Zoubin Ghahramani

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

Solving inverse problems using an EM approach to density estimation

Zoubin Ghahramani, Zoubin Ghahramani, 1993 .

Bayesian Monte Carlo

Carl E. Rasmussen, Zoubin Ghahramani, Zoubin Ghahramani, 2002, NIPS.

Factorial Learning and the EM Algorithm

Zoubin Ghahramani, Zoubin Ghahramani, 1994, NIPS.

Parameter estimation for linear dynamical systems

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 1996 .

The EM-EP algorithm for Gaussian process classification

Zoubin Ghahramani, Hc Kim, 2003 .

MCMC for Doubly-intractable Distributions

Zoubin Ghahramani, Iain Murray, David J. C. MacKay, 2006, UAI.

Scalable Variational Gaussian Process Classification

James Hensman, Zoubin Ghahramani, Alexander G. de G. Matthews, 2014, AISTATS.

Relational Learning with Gaussian Processes

Wei Chu, Zoubin Ghahramani, S. Sathiya Keerthi, 2006, NIPS.

The variational Bayesian EM algorithm for incomplete data: with application to scoring graphical model structures

Matthew J. Beal, Zoubin Ghahramani, 2003 .

Tree-Structured Stick Breaking Processes for Hierarchical Data

Michael I. Jordan, Ryan P. Adams, Zoubin Ghahramani, 2010, 1006.1062.

Statistical models for partial membership

Katherine A. Heller, Zoubin Ghahramani, Sinead Williamson, 2008, ICML '08.

The Infinite Factorial Hidden Markov Model

Yee Whye Teh, Zoubin Ghahramani, Jurgen Van Gael, 2008, NIPS.

Variational Inference for Bayesian Mixtures of Factor Analysers

Zoubin Ghahramani, Matthew J. Beal, Zoubin Ghahramani, 1999, NIPS.

Computational models of sensorimotor integration

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolptrt, 1997 .

MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES

Michael I. Jordan, Zoubin Ghahramani, Zoubin Ghahramani, 2001 .

Avoiding pathologies in very deep networks

Ryan P. Adams, Zoubin Ghahramani, David Duvenaud, 2014, AISTATS.

Modeling Dyadic Data with Binary Latent Factors

Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis, 2006, NIPS.

Switching State-Space Models

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 1996 .

SMEM Algorithm for Mixture Models

Geoffrey E. Hinton, Naonori Ueda, Zoubin Ghahramani, 1998, Neural Computation.

Propagation Algorithms for Variational Bayesian Learning

Zoubin Ghahramani, Matthew J. Beal, Zoubin Ghahramani, 2000, NIPS.

Time-Sensitive Dirichlet Process Mixture Models

J. Lafferty, Xiaojin Zhu, Zoubin Ghahramani, 2005 .

Model comparison

Zoubin Ghahramani, V. Prasuhn, R. Schulin, 2005 .

Infinite Sparse Factor Analysis and Infinite Independent Components Analysis

Zoubin Ghahramani, David A. Knowles, Zoubin Ghahramani, 2007, ICA.

Neural Adaptive Sequential Monte Carlo

Richard E. Turner, Zoubin Ghahramani, Shixiang Gu, 2015, NIPS.

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2009, UAI.

An internal model for sensorimotor integration.

Michael I. Jordan, D M Wolpert, Z Ghahramani, 1995, Science.

Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process

Zoubin Ghahramani, Finale Doshi-Velez, David A. Knowles, 2009, NIPS.

Accelerated sampling for the Indian Buffet Process

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2009, ICML '09.

Stick-breaking Construction for the Indian Buffet Process

Yee Whye Teh, Dilan Görür, Zoubin Ghahramani, 2007, AISTATS.

Learning from labeled and unlabeled data with label propagation

Zoubin Ghahramani, Xiaojin Zhu, Xiaojin Zhu, 2002 .

Infinite Mixtures of Gaussian Process Experts

Carl E. Rasmussen, Zoubin Ghahramani, Zoubin Ghahramani, 2001, NIPS.

Choosing a Variable to Clamp: Approximate Inference Using Conditioned Belief Propagation

Zoubin Ghahramani, F. Eaton, 2009 .

Dependent Indian Buffet Processes

Zoubin Ghahramani, Peter Orbanz, Sinead Williamson, 2010, AISTATS.

Identifying Protein Complexes in High-Throughput Protein Interaction Screens Using an Infinite Latent Feature Model

Wei Chu, Zoubin Ghahramani, David L. Wild, 2005, Pacific Symposium on Biocomputing.

Local and global sparse Gaussian process approximations

Zoubin Ghahramani, Edward Snelson, Zoubin Ghahramani, 2007, AISTATS.

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference pdf

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2015, ArXiv.

On the Convergence of Bound Optimization Algorithms

Zoubin Ghahramani, Ruslan Salakhutdinov, Sam T. Roweis, 2002, UAI.

Gaussian process regression with mismatched models

Thomas G. Dietterich, Zoubin Ghahramani, Suzanna Becker, 2002, Neural Information Processing Systems.

Turing: A Language for Flexible Probabilistic Inference

Zoubin Ghahramani, Kai Xu, Hong Ge, 2018 .

Variational Bayesian Learning

Zoubin Ghahramani, 2000, Variational Bayesian Learning Theory.

Training generative neural networks via Maximum Mean Discrepancy optimization

Zoubin Ghahramani, Gintare Karolina Dziugaite, Daniel M. Roy, 2015, UAI.

MetaGAN: An Adversarial Approach to Few-Shot Learning

Yoshua Bengio, Zoubin Ghahramani, Yangqiu Song, 2018, NeurIPS.

Variational Learning for Switching State-Space Models

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 2000, Neural Computation.

Propagating uncertainty in POMDP value iteration with Gaussian processes

Zoubin Ghahramani, E. Tuttle, 2004 .

Kronecker Graphs: An Approach to Modeling Networks pdf

Christos Faloutsos, Jure Leskovec, Deepayan Chakrabarti, 2008, J. Mach. Learn. Res..

Active Learning of Model Evidence Using Bayesian Quadrature

Carl E. Rasmussen, Roman Garnett, Zoubin Ghahramani, 2012, NIPS.

Learning Dynamic Bayesian Networks

Zoubin Ghahramani, Zoubin Ghahramani, 1997, Summer School on Neural Networks.

Warped Gaussian Processes

Carl E. Rasmussen, Zoubin Ghahramani, Edward Snelson, 2003, NIPS.

Learning to Parse Images

Yee Whye Teh, Geoffrey E. Hinton, Zoubin Ghahramani, 1999, NIPS.

Bayesian model search for mixture models based on optimizing variational bounds

Naonori Ueda, Zoubin Ghahramani, Zoubin Ghahramani, 2002, Neural Networks.

Simultaneous Localization and Mapping with Sparse Extended Information Filters

Hugh F. Durrant-Whyte, Zoubin Ghahramani, Andrew Y. Ng, 2004, Int. J. Robotics Res..

Automatic Construction and Natural-Language Description of Nonparametric Regression Models

Joshua B. Tenenbaum, Zoubin Ghahramani, Roger B. Grosse, 2014, AAAI.

MFDTs: mean field dynamic trees

Zoubin Ghahramani, Christopher K. I. Williams, Amos J. Storkey, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Warped Mixtures for Nonparametric Cluster Shapes pdf

Tomoharu Iwata, Zoubin Ghahramani, David Duvenaud, 2012, UAI.

Occam's Razor

Carl E. Rasmussen, Zoubin Ghahramani, Zoubin Ghahramani, 2000, NIPS.

Copula-based Kernel Dependency Measures pdf

Barnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider, 2012, ICML.

Testing a Bayesian Measure of Representativeness Using a Large Image Database

Thomas L. Griffiths, Joshua T. Abbott, Katherine A. Heller, 2011, NIPS.

Bayesian Active Learning for Classification and Preference Learning pdf

Zoubin Ghahramani, Neil Houlsby, Máté Lengyel, 2011, ArXiv.

Nonparametric Transforms of Graph Kernels for Semi-Supervised Learning

Zoubin Ghahramani, Xiaojin Zhu, John D. Lafferty, 2004, NIPS.

Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2015, NIPS.

The delve manual

Geoffrey E. Hinton, Robert Tibshirani, Zoubin Ghahramani, 1996 .

Proceedings of the 24th international conference on Machine learning

Zoubin Ghahramani, Zoubin Ghahramani, 2007, ICML 2007.

Sandwiching the marginal likelihood using bidirectional Monte Carlo pdf

Ryan P. Adams, Zoubin Ghahramani, Roger B. Grosse, 2015, ArXiv.

Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models

Carl E. Rasmussen, Zoubin Ghahramani, David L. Wild, 2003, Pacific Symposium on Biocomputing.

Motor learning models

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2006 .

SIGMa: simple greedy matching for aligning large knowledge bases

Gjergji Kasneci, Zoubin Ghahramani, Thore Graepel, 2012, KDD.

Spectral Methods for Automatic Multiscale Data Clustering

Zoubin Ghahramani, Arik Azran, Zoubin Ghahramani, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Variational Gaussian Dropout is not Bayesian

Zoubin Ghahramani, A. G. D. G. Matthews, Jiri Hron, 2017, 1711.02989.

Approximate inference for the loss-calibrated Bayesian

Zoubin Ghahramani, Ferenc Huszar, Simon Lacoste-Julien, 2011, AISTATS.

A study of the effect of JPG compression on adversarial images pdf

Zoubin Ghahramani, Gintare Karolina Dziugaite, Daniel M. Roy, 2016, ArXiv.

Deep Bayesian Active Learning with Image Data pdf

Zoubin Ghahramani, Yarin Gal, Riashat Islam, 2017, ICML.

Latent-Space Variational Bayes

Zoubin Ghahramani, Sung Yang Bang, JaeMo Sung, 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Beam sampling for the infinite hidden Markov model

Yee Whye Teh, Zoubin Ghahramani, Yunus Saatci, 2008, ICML '08.

Semi-supervised learning : from Gaussian fields to Gaussian processes

Zoubin Ghahramani, Xiaojin Zhu, John Lafferty, 2003 .

Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results

Hugh F. Durrant-Whyte, Zoubin Ghahramani, Andrew Y. Ng, 2004, WAFR.

Hidden Markov Decision Trees

Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul, 1996, NIPS.

Bayesian Classifier Combination

Hyun-Chul Kim, Zoubin Ghahramani, Zoubin Ghahramani, 2012, AISTATS.

Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling pdf

Zoubin Ghahramani, David A. Knowles, Zoubin Ghahramani, 2010, The Annals of Applied Statistics.

Distributed Inference for Dirichlet Process Mixture Models

Zoubin Ghahramani, Yutian Chen, Hong Ge, 2015, ICML.

Outlier Robust Learning Algorithm for Gaussian Process Classification

김현철, Zoubin Ghahramani, Zoubin Ghahramani, 2007 .

Biomarker discovery in microarray gene expression data with Gaussian processes

Wei Chu, Zoubin Ghahramani, Francesco Falciani, 2005, Bioinform..

Dynamic Covariance Models for Multivariate Financial Time Series

Zoubin Ghahramani, José Miguel Hernández-Lobato, Yue Wu, 2013, ICML.

Dropout as a Bayesian Approximation: Appendix

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2015, 1506.02157.

Branch-recombinant Gaussian processes for analysis of perturbations in biological time series

Zoubin Ghahramani, Christopher A. Penfold, Lorenz Wernisch, 2018, bioRxiv.

Bayesian inference of transcriptional branching identifies regulators of early germ cell development in humans

Christopher A. Penfold, John E. Reid, Zoubin Ghahramani, 2017, bioRxiv.

The Status of Structural Genomics Defined Through the Analysis of Current Targets and Structures

Tong Liu, Li Chen, Philip E. Bourne, 2003, Pacific Symposium on Biocomputing.

Cold-start Active Learning with Robust Ordinal Matrix Factorization

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2014, ICML.

Denotational validation of higher-order Bayesian inference

Ohad Kammar, Hongseok Yang, Zoubin Ghahramani, 2017, Proc. ACM Program. Lang..

Appearance-based gender classification with Gaussian processes

Hyun-Chul Kim, Zoubin Ghahramani, Daijin Kim, 2006, Pattern Recognition Letters.

Unsupervised and Constrained Dirichlet Process Mixture Models for Verb Clustering

Zoubin Ghahramani, A. Korhonen, Andreas Vlachos, 2009 .

Lost Relatives of the Gumbel Trick

Zoubin Ghahramani, Matej Balog, Nilesh Tripuraneni, 2017, ICML.

Hierarchical Non-linear Factor Analysis and Topographic Maps

Geoffrey E. Hinton, Zoubin Ghahramani, Zoubin Ghahramani, 1997, NIPS.

Gaussian Processes for Ordinal Regression

Wei Chu, Zoubin Ghahramani, Zoubin Ghahramani, 2005, J. Mach. Learn. Res..

Tree-Structured Stick Breaking for Hierarchical Data

Michael I. Jordan, Ryan P. Adams, Zoubin Ghahramani, 2010, NIPS.

Randomized algorithms for fast Bayesian hierarchical clustering

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2005 .

Towards semi-supervised classification with Markov random fields

Zoubin Ghahramani, Xiaojin Zhu, John Lafferty, 2002 .

A Generative Model of Vector Space Semantics

Jacob Andreas, Zoubin Ghahramani, Zoubin Ghahramani, 2013, CVSM@ACL.

Expectation Propagation for Infinite Mixtures

Zoubin Ghahramani, Thomas P. Minka, T. Minka, 2017 .

The Automatic Statistician

Zoubin Ghahramani, David Janz, Emma Smith, 2019, Automated Machine Learning.

Temporal processing with connectionist networks

Zoubin Ghahramani, R. B. Allen, R. Allen, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models

Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, Zoubin Ghahramani, 2009, J. Mach. Learn. Res..

Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

Kristian Kersting, Robert Peharz, Zoubin Ghahramani, 2019, UAI.

Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes

Tomoharu Iwata, Zoubin Ghahramani, Zoubin Ghahramani, 2017, 1707.05922.

Preference learning with Gaussian processes

Wei Chu, Zoubin Ghahramani, Zoubin Ghahramani, 2005, ICML.

Bayesian hierarchical clustering

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2005, ICML.

Quantifying mismatch in Bayesian optimization

José Miguel Hernández-Lobato, Zoubin Ghahramani, S. Gershman, 2016, NIPS 2016.

Computational principles of movement neuroscience

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2000, Nature Neuroscience.

Entropy and Mutual Information

Zoubin Ghahramani, .

A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views

Zoubin Ghahramani, Jennifer G. Dy, Donglin Niu, 2012, AISTATS.

Generalization to Local Remappings of the Visuomotor Coordinate Transformation

Michael I. Jordan, D M Wolpert, Z Ghahramani, 1996, The Journal of Neuroscience.

Computational motor control

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2004 .

A Bayesian approach to modelling uncertainty in gene expression clusters

Zoubin Ghahramani, C. Rasmussen, D. Wild, 2002 .

Structure Discovery in Nonparametric Regression through Compositional Kernel Search pdf

Joshua B. Tenenbaum, Zoubin Ghahramani, Roger B. Grosse, 2013, ICML.

Unifying linear dimensionality reduction

J. Cunningham, Zoubin Ghahramani, 2014 .

Antithetic and Monte Carlo kernel estimators for partial rankings

Arthur Gretton, Zoubin Ghahramani, Mark Rowland, 2018, Statistics and Computing.

Variational Bayesian dropout: pitfalls and fixes pdf

Zoubin Ghahramani, Jiri Hron, Alexander G. de G. Matthews, 2018, ICML.

A Bayesian network model for protein fold and remote homologue recognition

Zoubin Ghahramani, David L. Wild, A. Raval, 2002, Bioinform..

Discovering transcriptional modules by Bayesian data integration

Zoubin Ghahramani, Jim E. Griffin, David L. Wild, 2010, Bioinform..

Bayesian two-sample tests pdf

Zoubin Ghahramani, Karsten M. Borgwardt, Zoubin Ghahramani, 2009, ArXiv.

Unifying linear dimensionality reduction

Zoubin Ghahramani, John P. Cunningham, J. Cunningham, 2014, 1406.0873.

Output-Space Predictive Entropy Search for Flexible Global Optimization

Matthew W. Hoffman, Zoubin Ghahramani, 2016 .

Unsupervised Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2003, Advanced Lectures on Machine Learning.

A kernel method for unsupervised structured network inference

Zoubin Ghahramani, Oliver Stegle, Karsten M. Borgwardt, 2009, AISTATS.

A Very Simple Safe-Bayesian Random Forest

Zoubin Ghahramani, Novi Quadrianto, Zoubin Ghahramani, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Probabilistic Matrix Factorization with Non-random Missing Data

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2014, ICML.

Graphical models: parameter learning

Zoubin Ghahramani, Zoubin Ghahramani, 2002 .

Bayesian Sets

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2005, NIPS.

Probabilistic machine learning and artificial intelligence

Zoubin Ghahramani, Zoubin Ghahramani, 2015, Nature.

A bayesian view of motor adaptation

Zoubin Ghahramani, At Korenberg, 2002 .

Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2011, ICML.

Bayesian Gaussian Process Classification with the EM-EP Algorithm

Hyun-Chul Kim, Zoubin Ghahramani, Zoubin Ghahramani, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Sparse Parametric Gaussian Processes

Zoubin Ghahramani, Edward Snelson, 2005 .

Relational Learning and Network Modelling Using Infinite Latent Attribute Models

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

General Latent Feature Modeling for Data Exploration Tasks pdf

Zoubin Ghahramani, Isabel Valera, Melanie F. Pradier, 2017, ArXiv.

A Birth-Death Process for Feature Allocation

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2017, ICML.

A dependent partition-valued process for multitask clustering and time evolving network modelling

David A. Knowles, Zoubin Ghahramani, Konstantina Palla, 2013, 1303.3265.

Maps, Modules, and Internal Models in Human Motor Control

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 2000 .

Graph Kernels by Spectral Transforms

Zoubin Ghahramani, Xiaojin Zhu, John Lafferty, 2006, Semi-Supervised Learning.

Ergodic Measure Preserving Flows

Zoubin Ghahramani, José Miguel Hernández-Lobato, Yichuan Zhang, 2018 .

Computational Models of SensorimotorIntegrationZoubin Ghahramani

Zoubin Ghahramani, D. Wolpert, Michael I. Jordanz, 1997 .

Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction

Wei Chu, Zoubin Ghahramani, David L. Wild, 2006, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

6 LEARNING NONLINEAR DYNAMICAL SYSTEMS USING THE EXPECTATION – MAXIMIZATION ALGORITHM

Zoubin Ghahramani, S. Roweis, Zoubin Ghahramani, 2001 .

Learning about protein hydrogen bonding by minimizing contrastive divergence

Zoubin Ghahramani, David L Wild, Zoubin Ghahramani, 2006, Proteins.

Robust Estimation of Local Genetic Ancestry in Admixed Populations Using a Nonparametric Bayesian Approach

E. Xing, Zoubin Ghahramani, Kyung-ah Sohn, 2012, Genetics.

Bayes rule in perception, action and cognition

Zoubin Ghahramani, D. Wolpert, 2004 .

Classification using log Gaussian Cox processes

Zoubin Ghahramani, A. G. D. G. Matthews, A. G. Matthews, 2014, 1405.4141.

Graphical Models for Inference with Missing Data

Kilian Q. Weinberger, M. Welling, Zoubin Ghahramani, 2014 .

A Bayesian Unsupervised Learning Algorithm that Scales

Geoffrey E. Hinton, Zoubin Ghahramani, 2007 .

Scaling in a hierarchical unsupervised network

Geoffrey E. Hinton, Zoubin Ghahramani, At Korenberg, 1999 .

Interpretable Continual Learning

Richard E. Turner, Zoubin Ghahramani, Adrian Weller, 2018 .

Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks

Zoubin Ghahramani, A. G. D. G. Matthews, J. Bradshaw, 2017, 1707.02476.

Edinburgh Explorer Denotational validation of higher-order Bayesian inference

Sean K. Moss, KLAUS OSTERMANN, Zoubin Ghahramani, 2017 .

A Simple and General Exponential Family Framework for Partial Membership and Factor Analysis

Zoubin Ghahramani, 2014 .

Generalized Method-of-Moments for Rank Aggregation

L. Bottou, Z. Ghahramani, C. J. C. Burges, 2013 .

Chapter 9 The Automatic Statistician

Zoubin Ghahramani, David Janz, J. Lloyd, 2018 .

A Linear-Time Particle Gibbs Sampler for Infinite Hidden Markov Models

Zoubin Ghahramani, Nilesh Tripuraneni, Shane Gu, 2015 .

Expert Finding using discriminative infinite Hidden Markov Model

Jurgen Van Gael, Zoubin Ghahramani, Yunus Saatci, 2015 .

Beta diffusion trees and hierarchical feature allocations

David A. Knowles, Zoubin Ghahramani, Creighton Heaukulani, 2014, 1408.3378.

Pathological Properties of Deep Bayesian Hierarchies

Zoubin Ghahramani, J. Steinhardt, 2011 .

Dirichlet Fragmentation Processes

Zoubin Ghahramani, Y. Gal, Hong Ge, 2015, 1509.04781.

Sublinear-Time Approximate MCMC Transitions for Probabilistic Programs

Vikash K. Mansinghka, Zoubin Ghahramani, Yutian Chen, 2014, 1411.1690.

Appendix : Variational Bayesian dropout : pitfalls and fixes

Zoubin Ghahramani, A. G. D. G. Matthews, Jiri Hron, 2018 .

Proceedings, Twenty-Fourth International Conference on Machine Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2007 .

Unsupervised learning of sensory-motor synergies

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2003 .

An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process

Zoubin Ghahramani, David A. Knowles, Amar Shah, 2015, International Conference on Machine Learning.

MCMC parameter learning in spatial statistics

Zoubin Ghahramani, Iain Murray, Djc MacKay, 2006 .

Mixture models for learning from incomplete data

Michael I. Jordan, Zoubin Ghahramani, Zoubin Ghahramani, 1997, Annual Conference Computational Learning Theory.

Partial Membership and Factor Analysis

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2014, Handbook of Mixed Membership Models and Their Applications.

Adaptation to switching force fields

Zoubin Ghahramani, At Korenberg, Zoubin Ghahramani, 2001 .

Adaptative feedback control for non-stationary dynamics

Zoubin Ghahramani, At Korenberg, Zoubin Ghahramani, 2001 .

Bayesian Methods for Unsupervised Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2003 .

Probabilistic Models for Unsupervised Learning

Zoubin Ghahramani, Sam T. Roweis, S. Roweis, 1999 .

Introduction of New Associate Editors

David J. Fleet, David J. Kriegman, Zoubin Ghahramani, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007

Zoubin Ghahramani, Zoubin Ghahramani, 2007, ICML.

A Bayesian network approach to protein fold recognition

Zoubin Ghahramani, David L. Wild, Zoubin Ghahramani, 1998 .

Baysian Segmental Models for Protein Secondary Structure and Contact Map Prediction

Wei Chu, Zoubin Ghahramani, Alexei A. Podtelezhnikov, 2006 .

Editor's Note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010, IEEE Trans. Pattern Anal. Mach. Intell..

Degrees of freedom and hand synergies in manipulation tasks

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2000 .

Editor’s Note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Kernel conditional graphical models

Zoubin Ghahramani, Massimiliano Pontil, F Perez Cruz, 2007 .

Choosing a Variable to Clamp

Zoubin Ghahramani, Frederik Eaton, Zoubin Ghahramani, 2009, International Conference on Artificial Intelligence and Statistics.

Nonparametric Probabilistic Modelling

Zoubin Ghahramani, Zoubin Ghahramani, 2012 .

Bayesian Time Series Models: Nonparametric hidden Markov models

Zoubin Ghahramani, Jurgen Van Gael, Zoubin Ghahramani, 2011 .

Bayesian nonparametric latent feature models (with discussion)

Thomas L. Griffiths, Zoubin Ghahramani, Peter Sollich, 2006 .

State of the Journal

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2011, IEEE Trans. Pattern Anal. Mach. Intell..

Gender Detection using Machine Learning Techniques and Delaunay Triangulation

Zoubin Ghahramani, Hong Yan, S. Bang, 2016 .

Time for bayes: comments to Amari and Kohonen

Zoubin Ghahramani, Zoubin Ghahramani, 1999 .

Multiple linear controllers for nonlinear and nonstationary dynamics

Zoubin Ghahramani, Daniel M. Wolpert, Philipp Vetter, 2000 .

Efficient Bayesian hierarchical clustering for gene expression data

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2006 .

IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010 .

Probabilistic Models for Preference Learning

Zoubin Ghahramani, Zoubin Ghahramani, 2011 .

A theory of optimal motor-sensory primitives

Zoubin Ghahramani, Emanuel Todorov, E. Todorov, 2001 .

approach to modelling Bayesian non-parametrics and the probabilistic

Zoubin Ghahramani, Zoubin Ghahramani, 2013 .

Introduction of New Associate Editors

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Lecture 6: Hierarchical and Nonlinear Models

Zoubin Ghahramani, Zoubin Ghahramani, 2005 .

Turing: Composable inference for probabilistic programming

Kai Xu, Zoubin Ghahramani, Hong Ge, 2018, International Conference on Artificial Intelligence and Statistics.

Introduction of New Associate Editors

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]

Thomas G. Dietterich, Zoubin Ghahramani, Suzanna Becker, 2001, NIPS.

Computational principles of multisensory integration: studies of adaptation to novel visuo-auditory remappings

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolpert, 1995 .

A neural network for learning how to parse tree adjoining grammars

Zoubin Ghahramani, Zoubin Ghahramani, 1990 .

Bayesian Learning in Undirected Graphical Models

Zoubin Ghahramani, Iain Murray, Hc Kim, 2003 .

Introduction of New Associate Editors

David J. Fleet, David J. Kriegman, Zoubin Ghahramani, 2008, IEEE Trans. Pattern Anal. Mach. Intell..

Lecture 6: Graphical Models: Learning

Zoubin Ghahramani, Carl Edward Rasmussen, Zoubin Ghahramani, 2010 .

Bayesian hidden markov models and extensions: Invited talk

Zoubin Ghahramani, Zoubin Ghahramani, 2010 .

Modelling biological responses using gene expression profiling and linear dynamical systems

Zoubin Ghahramani, Francesco Falciani, David L. Wild, 2001 .

Bayesian and L$_\mathbf{1}$ Approaches to Sparse Unsupervised Learning

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2011 .

Face recognition based on separate lattice HMMs

Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, 2006 .

Active learning with mixture models

David A. Cohn, Michael I. Jordan, Zoubin Ghahramani, 1997 .

A Tutorial on Gaussian Processes (or why I don't use SVMs)

Zoubin Ghahramani, Zoubin Ghahramani, 2011 .

The training algorithm based on variational approximation for separable 2D-HMM

Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, 2003 .

A Bayesian approach to information retrieval from sets of items

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2006 .

Editor's Note

Jiri Matas, Zoubin Ghahramani, Sing Bing Kang, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Editor's Note

Jiri Matas, Zoubin Ghahramani, Ramin Zabih, 2010, IEEE Trans. Pattern Anal. Mach. Intell..

Endorsed By: Acl Siglex Acl Sigsem a Regression Model of Adjective-noun Compositionality in Distributional Semantics Semantic Composition with Quotient Algebras Expectation Vectors: a Semiotics Inspired Approach to Geometric Lexical-semantic Representation Sketch Techniques for Scaling Distributiona

Zoubin Ghahramani, Suresh Venkatasubramanian, Marco Baroni, 2022 .

Contrastive Learning Using Spectral Methods

Kilian Q. Weinberger, Zoubin Ghahramani, 2013 .

Branch-recombinant Gaussian processes for analysis of perturbations in biological time series

Christopher A. Penfold, John E. Reid, Zoubin Ghahramani, 2018, bioRxiv.

A Simple and General Exponential Family Framework for Partial Membership and Factor Analysis

Edoardo M. Airoldi, Stephen E. Fienberg, Katherine A. Heller, 2014 .

Non-parametric Bayesian Methods

Zoubin Ghahramani, 2006 .

Biomimetics: Nature-Based Innovation

Mike Fraser, Anthony G. Pipe, Peter Robinson, 2011 .

Affective robotics: Human motion and behavioural inspiration for safe cooperation between humans and humanoid assistive robots

Majid Mirmehdi, Mike Fraser, Anthony G. Pipe, 2011 .

MCMC for Doubly-intractable Distributions

Iain Murray, D. Mackay, Zoubin Ghahramani, 2006, UAI.

Linear dimensionality reduction: survey, insights, and generalizations

J. Cunningham, Zoubin Ghahramani, 2014, J. Mach. Learn. Res..

Editor’s Note

Jiri Matas, Max Welling, Sing Bing Kang, 2010, IEEE Trans. Pattern Anal. Mach. Intell..

Resource-Efficient Neural Networks for Embedded Systems

Zoubin Ghahramani, F. Pernkopf, Robert Peharz, 2020, ArXiv.

Imitation networks: Few-shot learning of neural networks from scratch pdf

Koh Takeuchi, Naonori Ueda, Tomoharu Iwata, 2018, ArXiv.

Few-shot learning of neural networks from scratch by pseudo example optimization

Koh Takeuchi, Naonori Ueda, Tomoharu Iwata, 2018, BMVC.

Practical probabilistic programming with monads

Zoubin Ghahramani, Adam Ścibior, Andrew D. Gordon, 2015, Haskell.

Ranking Relations using Analogies in Biological and Information Networks

Edoardo M. Airoldi, Katherine A. Heller, Zoubin Ghahramani, 2009, The annals of applied statistics.

Bayesian Cluster Analysis: Point Estimation and Credible Balls (with Discussion)

Zoubin Ghahramani, Sara Wade, Zoubin Ghahramani, 2015, Bayesian Analysis.

Computation and psychophysics of sensorimotor integration

Zoubin Ghahramani, Zoubin Ghahramani, 1996 .

Handling Incomplete Heterogeneous Data using VAEs pdf

Pablo M. Olmos, Zoubin Ghahramani, Isabel Valera, 2018, Pattern Recognit..

Bayesian inference of transcriptional branching identifies regulators of early germ cell development in humans

Christopher A. Penfold, John E. Reid, Zoubin Ghahramani, 2018, bioRxiv.

Bayesian non-parametrics and the probabilistic approach to modelling

Zoubin Ghahramani, Zoubin Ghahramani, 2013, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Statistical Model Criticism using Kernel Two Sample Tests

Zoubin Ghahramani, James Robert Lloyd, Zoubin Ghahramani, 2015, NIPS.

Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures

Stefanos Zafeiriou, Maja Pantic, Zoubin Ghahramani, 2013, ECML/PKDD.

Flexible latent variable models for multi-task learning

Yiming Yang, Zoubin Ghahramani, Jian Zhang, 2008, Machine Learning.

Conditional Graphical Models

Zoubin Ghahramani, Massimiliano Pontil, Fernando Perez-Cruz, 2007 .

An Introduction to Hidden Markov Models and Bayesian Networks

Zoubin Ghahramani, Zoubin Ghahramani, 2001, Int. J. Pattern Recognit. Artif. Intell..

General Latent Feature Models for Heterogeneous Datasets

Zoubin Ghahramani, Isabel Valera, Melanie F. Pradier, 2017, J. Mach. Learn. Res..

General Table Completion using a Bayesian Nonparametric Model

Zoubin Ghahramani, Isabel Valera, Zoubin Ghahramani, 2014, NIPS.

The Indian Buffet Process: An Introduction and Review

Thomas L. Griffiths, Zoubin Ghahramani, T. Griffiths, 2011, J. Mach. Learn. Res..

One-Network Adversarial Fairness

Zoubin Ghahramani, Adrian Weller, Isabel Valera, 2019, AAAI.

An Infinite Latent Attribute Model for Network Data

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2012, ICML.

GPflow: A Gaussian Process Library using TensorFlow

Alexis Boukouvalas, James Hensman, Zoubin Ghahramani, 2016, J. Mach. Learn. Res..

R/BHC: fast Bayesian hierarchical clustering for microarray data

Yang Xu, Katherine A. Heller, Zoubin Ghahramani, 2009, BMC Bioinformatics.

Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms pdf

Zoubin Ghahramani, Iain Murray, Iain Murray, 2004, UAI.

Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering pdf

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2013, UAI.

Determinantal clustering process - a nonparametric Bayesian approach to kernel based semi-supervised clustering

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2013, UAI 2013.

Probabilistic graphical models for semi-supervised traffic classification

Zoubin Ghahramani, Andrew W. Moore, Jurgen Van Gael, 2010, IWCMC.

Modeling T-cell activation using gene expression profiling and state-space models

Zoubin Ghahramani, Francesco Falciani, David L. Wild, 2004, Bioinform..

Modeling and Visualizing Uncertainty in Gene Expression Clusters Using Dirichlet Process Mixtures

Carl E. Rasmussen, Zoubin Ghahramani, David L. Wild, 2009, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

A Probabilistic Model for Online Document Clustering with Application to Novelty Detection

Yiming Yang, Zoubin Ghahramani, Jian Zhang, 2004, NIPS.

A nonparametric variable clustering model

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2012, NIPS.

Zoubin Ghahramani, Jim E. Griffin, Paul D. W. Kirk, 2012, Bioinform..

Tree-Based Inference for Dirichlet Process Mixtures

Yang Xu, Katherine A. Heller, Zoubin Ghahramani, 2009, AISTATS.

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series

Zoubin Ghahramani, Oliver Stegle, Karsten M. Borgwardt, 2009, RECOMB.

Modular decomposition in visuomotor learning

Zoubin Ghahramani, Daniel M. Wolpert, Zoubin Ghahramani, 1997, Nature.

Active Learning for Interactive Visualization

Tomoharu Iwata, Zoubin Ghahramani, Neil Houlsby, 2013, AISTATS.

Pareto Frontier Learning with Expensive Correlated Objectives

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2016, ICML.

Predictive Entropy Search for Efficient Global Optimization of Black-box Functions

Matthew W. Hoffman, Zoubin Ghahramani, José Miguel Hernández-Lobato, 2014, NIPS.

A General Framework for Constrained Bayesian Optimization using Information-based Search

Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani, 2015, J. Mach. Learn. Res..

Predictive Entropy Search for Bayesian Optimization with Unknown Constraints

Matthew W. Hoffman, Ryan P. Adams, Zoubin Ghahramani, 2015, ICML.

Variational Methods

Zoubin Ghahramani, Zoubin Ghahramani, 2014, Computer Vision, A Reference Guide.

Nested sampling for Potts models

Zoubin Ghahramani, Iain Murray, John Skilling, 2005, NIPS.

Forward dynamic models in human motor control: Psychophysical evidence

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolpert, 1994, NIPS.

Pitfalls in the use of Parallel Inference for the Dirichlet Process

Zoubin Ghahramani, Yarin Gal, Zoubin Ghahramani, 2014, ICML.

An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process pdf

Zoubin Ghahramani, David A. Knowles, Amar Shah, 2015, ICML 2015.

The Random Forest Kernel and other kernels for big data from random partitions pdf

Zoubin Ghahramani, Alex Davies, Zoubin Ghahramani, 2014, ArXiv.

A Bayesian approach to reconstructing genetic regulatory networks with hidden factors

Zoubin Ghahramani, Matthew J. Beal, Francesco Falciani, 2005, Bioinform..

Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series

Zoubin Ghahramani, Andrew Meade, Oliver Stegle, 2009, GCB.

Continuous Relaxations for Discrete Hamiltonian Monte Carlo

Yichuan Zhang, Zoubin Ghahramani, Charles A. Sutton, 2012, NIPS.

A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains

Zoubin Ghahramani, Finale Doshi-Velez, Zoubin Ghahramani, 2011, CogSci.

Bayesian Exponential Family PCA

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2008, NIPS.

Scaling the Indian Buffet Process via Submodular Maximization pdf

Zoubin Ghahramani, Colorado Reed, Zoubin Ghahramani, 2013, ICML.

Probabilistic Meta-Representations Of Neural Networks pdf

Peter Dayan, Zoubin Ghahramani, Theofanis Karaletsos, 2018, ArXiv.

Scalable Discrete Sampling as a Multi-Armed Bandit Problem

Zoubin Ghahramani, Yutian Chen, Zoubin Ghahramani, 2015, ICML.

Subsampling-Based Approximate Monte Carlo for Discrete Distributions pdf

Zoubin Ghahramani, Yutian Chen, Zoubin Ghahramani, 2015, ArXiv.

Learning Nonlinear Dynamical Systems Using an EM Algorithm

Zoubin Ghahramani, Sam T. Roweis, S. Roweis, 1998, NIPS.

Generalised Wishart Processes

Andrew Gordon Wilson, Zoubin Ghahramani, Zoubin Ghahramani, 2010, UAI.

Student-t Processes as Alternatives to Gaussian Processes

Andrew Gordon Wilson, Zoubin Ghahramani, Amar Shah, 2014, AISTATS.

Gaussian Process Regression Networks

Andrew Gordon Wilson, Zoubin Ghahramani, David A. Knowles, 2011, ICML.

Random function priors for exchangeable arrays with applications to graphs and relational data

Zoubin Ghahramani, Daniel M. Roy, Peter Orbanz, 2012, NIPS.

Collaborative Gaussian Processes for Preference Learning

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2012, NIPS.

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

Guy Van den Broeck, Kristian Kersting, Robert Peharz, 2020, ICML.

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic pdf

Sergey Levine, Richard E. Turner, Zoubin Ghahramani, 2016, ICLR.

Gaussian Process Behaviour in Wide Deep Neural Networks pdf

Richard E. Turner, Zoubin Ghahramani, Jiri Hron, 2018, ICLR.

On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes

James Hensman, Richard E. Turner, Zoubin Ghahramani, 2015, AISTATS.

Discovering Interpretable Representations for Both Deep Generative and Discriminative Models

Zoubin Ghahramani, Adrian Weller, Tameem Adel, 2018, ICML.

Archipelago: nonparametric Bayesian semi-supervised learning

Ryan P. Adams, Zoubin Ghahramani, Zoubin Ghahramani, 2009, ICML '09.

Predictive automatic relevance determination by expectation propagation

Yuan Qi, Zoubin Ghahramani, Tom Minka, 2004, ICML.

Dirichlet Process Mixture Models for Verb Clustering

Zoubin Ghahramani, Andreas Vlachos, Anna Korhonen, 2008 .

Randomized Nonlinear Component Analysis pdf

Bernhard Schölkopf, Alexander J. Smola, Zoubin Ghahramani, 2014, ICML.

Hidden Common Cause Relations in Relational Learning

Wei Chu, Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, 2007, NIPS.

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning

Richard E. Turner, Zoubin Ghahramani, Bernhard Scholkopf, 2017, NIPS.

Distributed Flexible Nonlinear Tensor Factorization

Zenglin Xu, Zoubin Ghahramani, Kai Zhang, 2016, NIPS.

Bilinear dynamical systems

Karl J. Friston, Z Ghahramani, K Friston, 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

Gaussian Process Volatility Model

Zoubin Ghahramani, José Miguel Hernández-Lobato, Yue Wu, 2014, NIPS.

Computational Structure of coordinate transformations: A generalization study

Michael I. Jordan, Zoubin Ghahramani, Daniel M. Wolpert, 1994, NIPS.

Model Reductions for Inference: Generality of Pairwise, Binary, and Planar Factor Graphs

Zoubin Ghahramani, Frederik Eaton, Zoubin Ghahramani, 2013, Neural Computation.

Probabilistic Models for Incomplete Multi-dimensional Arrays

Wei Chu, Zoubin Ghahramani, Zoubin Ghahramani, 2009, AISTATS.

Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices

Zoubin Ghahramani, José Miguel Hernández-Lobato, Neil Houlsby, 2014, ICML.

Real-time control of radiofrequency ablation by three-dimensional echo decorrelation imaging

T. D. Mast, Zoubin Ghahramani, P. Grimm, 2020 .

Gaussian Process Vine Copulas for Multivariate Dependence

Zoubin Ghahramani, David Lopez-Paz, José Miguel Hernández-Lobato, 2013, ICML.

Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data

Zoubin Ghahramani, Yutian Chen, Yarin Gal, 2015, ICML.

Bayesian and L1 Approaches to Sparse Unsupervised Learning pdf

Katherine A. Heller, Zoubin Ghahramani, Shakir Mohamed, 2011, ICML 2012.

Magnetic Hamiltonian Monte Carlo

Richard E. Turner, Zoubin Ghahramani, Nilesh Tripuraneni, 2016, ICML.

A graphical model for protein secondary structure prediction

Wei Chu, Zoubin Ghahramani, David L. Wild, 2004, ICML.

Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models

Wei Chu, Zoubin Ghahramani, David L. Wild, 2004, ESANN.

Metropolis Algorithms for Representative Subgraph Sampling

Hans-Peter Kriegel, Zoubin Ghahramani, Karsten M. Borgwardt, 2008, 2008 Eighth IEEE International Conference on Data Mining.

Optimization with EM and Expectation-Conjugate-Gradient

Zoubin Ghahramani, Ruslan Salakhutdinov, Sam T. Roweis, 2003, ICML.

A new approach to data driven clustering

Zoubin Ghahramani, Arik Azran, Zoubin Ghahramani, 2006, ICML.

The Mirage of Action-Dependent Baselines in Reinforcement Learning pdf

Sergey Levine, Richard E. Turner, Zoubin Ghahramani, 2018, ICML.

Interpretability Constraints and Trade-offs in Using Mixed Membership Models

S. Fienberg, E. Erosheva, Zoubin Ghahramani, 2014 .

Computational neuroscience: Building blocks of movement

Zoubin Ghahramani, Zoubin Ghahramani, 2000, Nature.

Functional programming for modular Bayesian inference

Ohad Kammar, Zoubin Ghahramani, Adam Scibior, 2018, Proc. ACM Program. Lang..

Beta Diffusion Trees

Zoubin Ghahramani, David A. Knowles, Creighton Heaukulani, 2014, ICML.

Accelerating Bayesian Hierarchical Clustering of Time Series Data with a Randomised Algorithm

Zoubin Ghahramani, David L. Wild, Richard S. Savage, 2013, PloS one.

The Mondrian Kernel

Yee Whye Teh, Zoubin Ghahramani, Daniel M. Roy, 2016, UAI.

Automatic Bayesian Density Analysis pdf

Kristian Kersting, Robert Peharz, Zoubin Ghahramani, 2018, AAAI.

Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects pdf

Zoubin Ghahramani, Mingshi Wang, Will Y. Zou, 2020, ArXiv.

Face Recognition Based on Separable Lattice HMMS

Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamura, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Bayesian Generalised Ensemble Markov Chain Monte Carlo

Ole Winther, Zoubin Ghahramani, Jes Frellsen, 2016, AISTATS.

Bayesian Support Vector Machines for Feature Ranking and Selection

Wei Chu, Zoubin Ghahramani, S. Sathiya Keerthi, 2006, Feature Extraction.

Gene function prediction from synthetic lethality networks via ranking on demand

Zoubin Ghahramani, Karsten M. Borgwardt, Christoph Lippert, 2010, Bioinform..

Variational Infinite Hidden Conditional Random Fields

Stefanos Zafeiriou, Maja Pantic, Zoubin Ghahramani, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Proceedings of the 24th international conference on Machine learning

Zoubin Ghahramani, 2007, ICML 2007.

Predicting Structured Data

Gökhan BakIr, Sundar Vishwanathan, Bernhard Schölkopf, 2008 .

Efficient and Robust Machine Learning for Real-World Systems pdf

Holger Fröning, Sebastian Tschiatschek, Franz Pernkopf, 2018, ArXiv.

Advances in Neural Information Processing Systems 25

Yichuan Zhang, Charles Sutton, Charles Sutton, 2012 .

Compact approximations to Bayesian predictive distributions

Zoubin Ghahramani, Edward Snelson, Zoubin Ghahramani, 2005, ICML.

Learning the Structure of Deep Sparse Graphical Models

Ryan P. Adams, Zoubin Ghahramani, Hanna M. Wallach, 2009, AISTATS.

MCMC for Variationally Sparse Gaussian Processes

James Hensman, Zoubin Ghahramani, Maurizio Filippone, 2015, NIPS.

Reinforcement Learning by Probability Matching

Michael I. Jordan, Philip N. Sabes, Zoubin Ghahramani, 1995, NIPS 1995.

A Probabilistic Model for Dirty Multi-task Feature Selection

Daniel Hernández-Lobato, Zoubin Ghahramani, José Miguel Hernández-Lobato, 2015, ICML.

Scaling the iHMM: Parallelization versus Hadoop

Zoubin Ghahramani, Andreas Vlachos, Jurgen Van Gael, 2010, 2010 10th IEEE International Conference on Computer and Information Technology.

Reconstructing Transcriptional Networks Using Gene Expression Profiling and Bayesian State-Space Models

Juan Li, Zoubin Ghahramani, Matthew J. Beal, 2007 .

Modeling genetic regulatory networks using gene expression profiling and state space models

Zoubin Ghahramani, David L. Wild, John E. Angus, 2005 .

Variable Noise and Dimensionality Reduction for Sparse Gaussian processes pdf

Zoubin Ghahramani, Edward Snelson, Zoubin Ghahramani, 2006, UAI.

Markov Beta Processes for Time Evolving Dictionary Learning

Zoubin Ghahramani, Amar Shah, Zoubin Ghahramani, 2016, UAI.

U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models

Zoubin Ghahramani, Seungjin Choi, Sung Yang Bang, 2005, ECML.

[4] N. Friedman, M. Linial, I. Nachman, and D. Pe’er. Using Bayesian networks

Michael I. Jordan, Zoubin Ghahramani, B. Engelhardt, 2009 .

Outlier Robust Gaussian Process Classification

Hyun-Chul Kim, Zoubin Ghahramani, Zoubin Ghahramani, 2008, SSPR/SPR.

Factorial Hidden Markov Models

Matthew J. Beal, Zoubin Ghahramani, C. Rasmussen, 2004, Machine Learning.

Factorial Hidden Markov Models

Michael I. Jordan, Zoubin Ghahramani, 2004, Machine Learning.

Slice Sampling for Probabilistic Programming pdf

Zoubin Ghahramani, Razvan Ranca, Zoubin Ghahramani, 2015, ArXiv.

Analogical Reasoning with Relational Bayesian Sets

Katherine A. Heller, Zoubin Ghahramani, Ricardo Bezerra de Andrade e Silva, 2007, AISTATS.

A Simple Bayesian Framework for Content-Based Image Retrieval

Katherine A. Heller, Zoubin Ghahramani, Zoubin Ghahramani, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Improving PPM with Dynamic Parameter Updates

Zoubin Ghahramani, David J. C. MacKay, Christian Steinruecken, 2015, 2015 Data Compression Conference.

Proceedings of the 14th International Conference on Neural Information Processing Systems: Natural and Synthetic

Thomas G. Dietterich, Z. Ghahramani, S. Becker, 2001 .

Copula Processes

Andrew Gordon Wilson, Zoubin Ghahramani, Zoubin Ghahramani, 2010, NIPS.

Reinforcement Learning by Probability Matching

Michael I. Jordan, Zoubin Ghahramani, 1995, NIPS 1995.

Bayesian inference on random simple graphs with power law degree distributions

Zoubin Ghahramani, Seungjin Choi, Juho Lee, 2017, ICML.

Advances in Neural Information Processing Systems 18

Zoubin Ghahramani, J. Skilling, I. Murray, 2006 .

Unsupervised Many-to-Many Object Matching for Relational Data

Tomoharu Iwata, Zoubin Ghahramani, James Robert Lloyd, 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

The variational Kalman smoother

Zoubin Ghahramani, Matthew J. Beal, Zoubin Ghahramani, 2001 .

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference

Zoubin Ghahramani, Y. Gal, 2015, ArXiv.

A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response

Zoubin Ghahramani, Richard Yi Da Xu, Massimo Piccardi, 2014, AISTATS.

Robust Estimation of Local Genetic Ancestry in Admixed Populations Using a Nonparametric Bayesian Approach

E. Xing, Zoubin Ghahramani, Kyung-ah Sohn, 2012, Genetics.

Reinforcement Learning by Probability Matching

Michael I. Jordan, Zoubin Ghahramani, 1995, NIPS.

MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES

Michael I. Jordan, Tommi S. Jaakkola, Matthew J. Beal, 1996 .

Pattern classification using a mixture of factor analyzers

Geoffrey E. Hinton, Naonori Ueda, Zoubin Ghahramani, 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

A reversible infinite HMM using normalised random measures

Zoubin Ghahramani, David A. Knowles, Konstantina Palla, 2014, ICML.

Nonparametric Bayesian inference of transcriptional branching and recombination identifies regulators of early human germ cell development

Christopher A. Penfold, John E. Reid, Zoubin Ghahramani, 2017 .

A note on the evidence and Bayesian Occam's razor

Zoubin Ghahramani, Iain Murray, Iain Murray, 2005 .

One-Shot Learning in Discriminative Neural Networks pdf

Zoubin Ghahramani, James Robert Lloyd, Jordan Burgess, 2017, ArXiv.

A Non-Parametric Bayesian Method for Inferring Hidden Causes

T. Griffiths, Zoubin Ghahramani, F. Wood, 2006, UAI.

Interpretability of Mixed Membership Models

Zoubin Ghahramani, 2014, Handbook of Mixed Membership Models and Their Applications.

An Infinite Latent Attribute Model for Network Data

David A. Knowles, Zoubin Ghahramani, Konstantina Palla, 2012, ICML.

Probabilistic Independence Networks for Hidden Markov Probability Models

Michael I. Jordan, Padhraic Smyth, David Heckerman, 1997, Neural Computation.

Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks

Zoubin Ghahramani, Creighton Heaukulani, Zoubin Ghahramani, 2013, ICML.

The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models pdf

Zoubin Ghahramani, David A. Knowles, Novi Quadrianto, 2013, UAI.

Probabilistic Matrix Factorization with Non-random Missing Data

José Miguel Hernández-Lobato, Zoubin Ghahramani, N. Houlsby, 2014, International Conference on Machine Learning.

Expectation-conjugate gradient: An alternative to EM

R. Salakhutdinov, S. Roweis, Zoubin Ghahramani, 2002 .

Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates

Geoffrey E. Hinton, R. Nakano, Z. Ghahramani, 1998, Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378).

Graphical Models for Inference with Missing Data

Jin Tian, Kilian Q. Weinberger, Judea Pearl, 2013, NIPS.

Probabilistic models for data combination in recommender systems

Zoubin Ghahramani, Sinead Williamson, Zoubin Ghahramani, 2008 .

Cold-start Active Learning with Robust Ordinal Matrix Factorization

José Miguel Hernández-Lobato, Zoubin Ghahramani, N. Houlsby, 2014, ICML.

Bayesian Cluster Analysis: Point Estimation and Credible Balls (with Discussion)

Zoubin Ghahramani, S. Wade, 2015, Bayesian Analysis.