Volker Tresp

Volker Tresp, Evgeniy Faerman, Max Berrendorf, 2020, 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT).

Towards LarKC: A Platform for Web-Scale Reasoning

Dieter Fensel, Frank van Harmelen, Lael J. Schooler, 2008, 2008 IEEE International Conference on Semantic Computing.

GPPS: A Gaussian Process Positioning System for Cellular Networks

Anton Schwaighofer, Volker Tresp, Marian Grigoras, 2003, NIPS.

The Bayesian Committee Support Vector Machine

Anton Schwaighofer, Volker Tresp, Volker Tresp, 2001, ICANN.

Transductive Experiment Design

Volker Tresp, Kai Yu, 2005 .

Big Data: Practical Applications [Scanning the Issue]

Jon Atli Benediktsson, Simon Haykin, Volker Tresp, 2016, Proc. IEEE.

Towards a New Science of a Clinical Data Intelligence pdf

Volker Tresp, Denis Krompass, Volker Tresp, 2013, ArXiv.

Factorizing YAGO: scalable machine learning for linked data

Hans-Peter Kriegel, Volker Tresp, Maximilian Nickel, 2012, WWW.

The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging

Peter Mayer, Anton Schwaighofer, Volker Tresp, 2002, NIPS.

A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose Prediction

Volker Tresp, Thomas Briegel, Volker Tresp, 1997, NIPS.

Type-Constrained Representation Learning in Knowledge Graphs

Volker Tresp, Denis Krompass, Stephan Baier, 2015, SEMWEB.

Robust Neural Network Regression for Offline and Online Learning

Volker Tresp, Thomas Briegel, 1999, NIPS.

Natural Language Questions for the Web of Data

Gerhard Weikum, Mohamed Yahya, Klaus Berberich, 2012, EMNLP.

Detecting a fraudulent call by means of a neural network

Volker Tresp, Michiaki Taniguchi, Volker Tresp, 1997 .

Probabilistic Hoeffding Trees - Sped-Up Convergence and Adaption of Online Trees on Changing Data Streams

Volker Tresp, Jonathan Boidol, Andreas Hapfelmeier, 2015, ICDM.

Semantics for Global and Local Interpretation of Deep Neural Networks pdf

Volker Tresp, Jindong Gu, Volker Tresp, 2019, ArXiv.

Hierarchy-regularized latent semantic indexing

Hans-Peter Kriegel, Volker Tresp, Shipeng Yu, 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

Classification with missing and uncertain inputs

Volker Tresp, Subutai Ahmad, Volker Tresp, 1993, IEEE International Conference on Neural Networks.

Context-aware tensor decomposition for relation prediction in social networks

Achim Rettinger, Volker Tresp, Yi Huang, 2012, Social Network Analysis and Mining.

Supervised probabilistic principal component analysis

Hans-Peter Kriegel, Volker Tresp, Shipeng Yu, 2006, KDD '06.

Efficient Dialog Policy Learning via Positive Memory Retention

Volker Tresp, Rui Zhao, Volker Tresp, 2018, 2018 IEEE Spoken Language Technology Workshop (SLT).

Incorporating prior knowledge into networks of locally-tuned units

Volker Tresp, Martin Röscheisen, Reimer Hofmann, 1994, COLT 1994.

Going Digital: A Survey on Digitalization and Large-Scale Data Analytics in Healthcare

J. Marc Overhage, Volker Tresp, Shipeng Yu, 2016, Proceedings of the IEEE.

Learning Initial Trust Among Interacting Agents

Achim Rettinger, Volker Tresp, Matthias Nickles, 2007, CIA.

Averaging Regularized Estimators

Volker Tresp, Michiaki Taniguchi, 1997, Neural Computation.

Machine Learning and Knowledge Discovery in Databases

Pauli Miettinen, Gemma C. Garriga, Bettina Berendt, 2016, Lecture Notes in Computer Science.

Integrating Ontological Prior Knowledge into Relational Learning

Volker Tresp, Max Planck, Stefan Reckow, 2008 .

Network Structuring and Training Using Rule-Based Knowledge

Volker Tresp, Subutai Ahmad, Jürgen Hollatz, 1992, NIPS.

Multi-output regularized projection

Volker Tresp, Shipeng Yu, Kai Yu, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

Die besonderen Eigenschaften Neuronaler Netze bei der Approximation von Funktionen

Volker Tresp, Volker Tresp, 1995, Künstliche Intell..

Relational Models

Volker Tresp, Maximilian Nickel, Volker Tresp, 2016, Encyclopedia of Social Network Analysis and Mining.

Hierarchical Bayesian modelling with Gaus-sian processes

Anton Schwaighofer, Volker Tresp, Kevin C. Yu, 2005, NIPS 2005.

Nonlinear Markov Networks for Continuous Variables

Volker Tresp, Reimar Hofmann, Volker Tresp, 1997, NIPS.

Push it to the Limit: Discover Edge-Cases in Image Data with Autoencoders pdf

Volker Tresp, Ilja Manakov, Volker Tresp, 2019, ArXiv.

Learning to Propagate Knowledge in Web Ontologies

Nicola Fanizzi, Claudia d'Amato, Volker Tresp, 2014, URSW.

Embedding Mapping Approaches for Tensor Factorization and Knowledge Graph Modelling

Volker Tresp, Yinchong Yang, Cristóbal Esteban, 2016, ESWC.

Towards Machine Learning on the Semantic Web

Achim Rettinger, Volker Tresp, Markus Bundschus, 2008, URSW.

Robust multi-task learning with t-processes

Volker Tresp, Shipeng Yu, Kai Yu, 2007, ICML '07.

Learning Gaussian processes from multiple tasks

Anton Schwaighofer, Volker Tresp, Kai Yu, 2005, ICML.

Improving Goal-Oriented Visual Dialog Agents via Advanced Recurrent Nets with Tempered Policy Gradient pdf

Volker Tresp, Rui Zhao, 2018, LaCATODA@IJCAI.

A Recommender System for Complex Real-World Applications with Nonlinear Dependencies and Knowledge Graph Context

Volker Tresp, Ingo Thon, Mitchell Joblin, 2019, ESWC.

The Tensor Memory Hypothesis pdf

Volker Tresp, Yunpu Ma, Volker Tresp, 2017, ArXiv.

Dirichlet enhanced relational learning

Hans-Peter Kriegel, Volker Tresp, Shipeng Yu, 2005, ICML '05.

Predictive Modeling of Therapy Decisions in Metastatic Breast Cancer with Recurrent Neural Network Encoder and Multinomial Hierarchical Regression Decoder

Volker Tresp, Peter A. Fasching, Yinchong Yang, 2017, 2017 IEEE International Conference on Healthcare Informatics (ICHI).

Advances in neural information processing systems : proceedings of the ... conference

Thomas G. Dietterich, Richard P. Lippmann, Klaus-Robert Müller, 1989 .

Embedding Learning for Declarative Memories

Volker Tresp, Yunpu Ma, Yinchong Yang, 2017, ESWC.

Contextual Prediction Difference Analysis pdf

Volker Tresp, Jindong Gu, Volker Tresp, 2019, ArXiv.

Mixture Approximations to Bayesian Networks pdf

Volker Tresp, Reimar Hofmann, Michael Haft, 1999, UAI.

A learning vector quantization algorithm for probabilistic models

Olli Simula, Volker Tresp, Jaakko Hollmén, 2000, 2000 10th European Signal Processing Conference.

Tutorial summary: Learning with dependencies between several response variables

Volker Tresp, Kai Yu, Volker Tresp, 2009, ICML '09.

Curiosity-Driven Experience Prioritization via Density Estimation pdf

Volker Tresp, Rui Zhao, Volker Tresp, 2018, ArXiv.

Mining the Semantic Web

Achim Rettinger, Nicola Fanizzi, Claudia d'Amato, 2012, Data Mining and Knowledge Discovery.

Meta-Classification using SVM Classifiers for Text Documents

Volker Tresp, Daniel Morariu, Lucian Vintan, 2008 .

Predicting Sequences of Clinical Events by Using a Personalized Temporal Latent Embedding Model

Volker Tresp, Danilo Schmidt, Denis Krompaß, 2015, 2015 International Conference on Healthcare Informatics.

Nonparametric Relational Learning for Social Network Analysis

Volker Tresp, Shipeng Yu, Zhao Xu, 2008 .

Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual Information

Hans-Peter Kriegel, Xueyan Jiang, Volker Tresp, 2012, ECML/PKDD.

Learning Goal-Oriented Visual Dialog via Tempered Policy Gradient

Volker Tresp, Rui Zhao, Volker Tresp, 2018, 2018 IEEE Spoken Language Technology Workshop (SLT).

Predictive Clinical Decision Support System with RNN Encoding and Tensor Decoding pdf

Volker Tresp, Peter A. Fasching, Yinchong Yang, 2016, ArXiv.

Statistical relational learning of trust

Achim Rettinger, Volker Tresp, Matthias Nickles, 2011, Machine Learning.

Reality mining on micropost streams - Deductive and inductive reasoning for personalized and location-based recommendations

Seon-Ho Kim, Emanuele Della Valle, Volker Tresp, 2014, Semantic Web.

Tailored-to-Fit Bayesian Network Modeling of Expert Diagnostic Knowledge

Dragan Obradovic, Ruxandra Lupas Scheiterer, Volker Tresp, 2007, J. VLSI Signal Process..

Statistical Relational Learning

Volker Tresp, Volker Tresp, 2014, Encyclopedia of Social Network Analysis and Mining.

Knowing a tree from the forest: art image retrieval using a society of profiles

Hans-Peter Kriegel, Wei-Ying Ma, Xiaofei He, 2003, MULTIMEDIA '03.

Saliency Methods for Explaining Adversarial Attacks pdf

Volker Tresp, Jindong Gu, Volker Tresp, 2019, ArXiv.

Statistical Relational Learning with Formal Ontologies

Achim Rettinger, Volker Tresp, Matthias Nickles, 2009, ECML/PKDD.

Large-scale factorization of type-constrained multi-relational data

Volker Tresp, Denis Krompass, Maximilian Nickel, 2014, 2014 International Conference on Data Science and Advanced Analytics (DSAA).

Location-Based Mobile Recommendations by Hybrid Reasoning on Social Media Streams

Emanuele Della Valle, Seon-Ho Kim, Volker Tresp, 2013, JIST.

Semi-Supervised Outlier Detection Using a Generative and Adversary Framework

Volker Tresp, Matthias Schubert, Jindong Gu, 2018 .

The Tensor Brain: Semantic Decoding for Perception and Memory pdf

Volker Tresp, Yunpu Ma, Sahand Sharifzadeh, 2020, ArXiv.

A nonparametric hierarchical bayesian framework for information filtering

Volker Tresp, Shipeng Yu, Kai Yu, 2004, SIGIR '04.

Transductive and Inductive Methods for Approximate Gaussian Process Regression

Anton Schwaighofer, Volker Tresp, Volker Tresp, 2002, NIPS.

Querying the Web with Statistical Machine Learning

Volker Tresp, Yi Huang, Maximilian Nickel, 2014, Towards the Internet of Services.

Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152)

Anima Anandkumar, Volker Tresp, Sebnem Rusitschka, 2016, Dagstuhl Reports.

Mixtures of Gaussian Processes

Volker Tresp, Volker Tresp, 2000, NIPS.

Early Brain Damage

Volker Tresp, Ralph Neuneier, Hans-Georg Zimmermann, 1996, NIPS.

Classification of rheumatoid joint inflammation based on laser imaging

Peter Mayer, Anton Schwaighofer, Volker Tresp, 2003, IEEE Transactions on Biomedical Engineering.

Improving Visual Relation Detection using Depth Maps pdf

Volker Tresp, Max Berrendorf, Sahand Sharifzadeh, 2019, 2020 25th International Conference on Pattern Recognition (ICPR).

Modeling and Learning Context-Aware Recommendation Scenarios Using Tensor Decomposition

Achim Rettinger, Volker Tresp, Hendrik Wermser, 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

Few-Shot One-Class Classification via Meta-Learning pdf

Volker Tresp, Ahmed Frikha, Denis Krompaß, 2019, AAAI.

Training Neural Networks with Deficient Data

Volker Tresp, Subutai Ahmad, Ralph Neuneier, 1993, NIPS.

Mining functional modules in genetic networks with decomposable graphical models.

Anton Schwaighofer, Volker Tresp, Mathäus Dejori, 2004, Omics : a journal of integrative biology.

Making Sense of Location-based Micro-posts Using Stream Reasoning

Emanuele Della Valle, Volker Tresp, Irene Celino, 2011, #MSM.

Logistic Tensor Factorization for Multi-Relational Data pdf

Volker Tresp, Maximilian Nickel, Volker Tresp, 2013, ArXiv.

Multi-Relational Learning with Gaussian Processes

Kristian Kersting, Volker Tresp, Zhao Xu, 2009, IJCAI.

Fast Inference in Infinite Hidden Relational Models

Hans-Peter Kriegel, Volker Tresp, Shipeng Yu, 2007, MLG.

Active Learning for Entity Alignment pdf

Volker Tresp, Evgeniy Faerman, Max Berrendorf, 2020, ECIR.

A Bayesian Committee Machine

Volker Tresp, Volker Tresp, 2000, Neural Computation.

Combining Regularized Neural Networks

Volker Tresp, Michiaki Taniguchi, 1997, ICANN.

Representation Learning for the Semantic Web

Heiko Paulheim, Volker Tresp, Zhiyuan Liu, 2020, J. Web Semant..

Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes

Wei-Ying Ma, Anton Schwaighofer, Volker Tresp, 2002, UAI.

Learning with Knowledge Graphs

Volker Tresp, Yunpu Ma, Stephan Baier, 2017, NeSy.

Tensor Decompositions for Modeling Inverse Dynamics pdf

Volker Tresp, Stephan Baier, 2017, ArXiv.

A Review of Relational Machine Learning for Knowledge Graphs

Evgeniy Gabrilovich, Volker Tresp, Kevin Murphy, 2015, Proceedings of the IEEE.

Efficient Methods for Dealing with Missing Data in Supervised Learning

Volker Tresp, Subutai Ahmad, Ralph Neuneier, 1994, NIPS.

Challenging the Internet of the Future with Urban Computing

Yi Huang, Zhisheng Huang, Emanuele Della Valle, 2008 .

Collaborative ordinal regression

Hans-Peter Kriegel, Volker Tresp, Shipeng Yu, 2006, ICML.

A hidden Markov model for metric and event-based data

Volker Tresp, Jaakko Hollmén, 2000, 2000 10th European Signal Processing Conference.

Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model

Volker Tresp, Jaakko Hollmén, Volker Tresp, 1998, NIPS.

Holistic Representations for Memorization and Inference

Volker Tresp, Yunpu Ma, Marcel Hildebrandt, 2018, UAI.

Improving Information Extraction from Images with Learned Semantic Models pdf

Volker Tresp, Yunpu Ma, Stephan Baier, 2018, IJCAI.

Generative binary codes

Volker Tresp, Reimar Hofmann, Michael Haft, 2003, Formal Pattern Analysis & Applications.

Multi-Output Regularized Feature Projection

Hans-Peter Kriegel, Volker Tresp, Shipeng Yu, 2006, IEEE Transactions on Knowledge and Data Engineering.

A statistical relational model for trust learning

Achim Rettinger, Volker Tresp, Matthias Nickles, 2008, AAMAS.

Digging for knowledge with information extraction: a case study on human gene-disease associations

Hans-Peter Kriegel, Laura Inés Furlong, Volker Tresp, 2010, CIKM '10.

Reasoning on Knowledge Graphs with Debate Dynamics pdf

Volker Tresp, Yunpu Ma, Mitchell Joblin, 2020, AAAI.

Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA

Thomas G. Dietterich, Volker Tresp, T. K. Leen, 2001, NIPS.

Tensor Factorization for Multi-relational Learning

Volker Tresp, Maximilian Nickel, Volker Tresp, 2013, ECML/PKDD.

Graphical Models for Relations - Modeling Relational Context

Xueyan Jiang, Achim Rettinger, Volker Tresp, 2011, KDIR.

Emergence of Motion-sensitive Neurons Properties by Learning Sparse Code for Natural Moving Images

Thomas G. Dietterich, Volker Tresp, Christophe Giraud-Carrier, 2001 .

Materializing and Querying Learned Knowledge

Achim Rettinger, Volker Tresp, Markus Bundschus, 2009 .

A Probabilistic Clustering-Projection Model for Discrete Data

Hans-Peter Kriegel, Volker Tresp, Shipeng Yu, 2005, PKDD.

Integrating Rule-Based Knowledge into Neural Computing

Volker Tresp, Jürgen Hollatz, 1992, DAGM-Symposium.

Remaining Useful Life Estimation for Unknown Motors Using a Hybrid Modeling Approach

Volker Tresp, Roland Wüchner, Michael Heizmann, 2019, 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).

Learning representations for discrete sensor networks using tensor decompositions

Volker Tresp, Denis Krompass, Stephan Baier, 2016, 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).

Exploiting Latent Embeddings of Nominal Clinical Data for Predicting Hospital Readmission

Volker Tresp, Thomas Ganslandt, Martin Sedlmayr, 2015, KI - Künstliche Intelligenz.

Social Network Mining with Nonparametric Relational Models

Kristian Kersting, Achim Rettinger, Volker Tresp, 2008, SNAKDD.

Combining Estimators Using Non-Constant Weighting Functions

Volker Tresp, Michiaki Taniguchi, Volker Tresp, 1994, NIPS.

Infinite Hidden Relational Models pdf

Hans-Peter Kriegel, Volker Tresp, Kai Yu, 2006, UAI.

Stochastic Relational Models for Discriminative Link Prediction

Wei Chu, Volker Tresp, Shipeng Yu, 2006, NIPS.

Categorical EHR Imputation with Generative Adversarial Nets

Volker Tresp, Yinchong Yang, Zhiliang Wu, 2019, 2019 IEEE International Conference on Healthcare Informatics (ICHI).

Embedding models for episodic knowledge graphs

Volker Tresp, Yunpu Ma, Erik Daxberger, 2018, J. Web Semant..

Embedding Models for Episodic Memory pdf

Volker Tresp, Yunpu Ma, Erik Daxberger, 2018, ArXiv.

Semantic Traffic-Aware Routing Using the LarKC Platform

Florian Steinke, Emanuele Della Valle, Volker Tresp, 2011, IEEE Internet Computing.

Knowledge Acquisition and Automated Generation of Bayesian Networks for a Medical Dialogue and Advisory System

Thomas Birkhölzer, Ruxandra Lupas Scheiterer, Volker Tresp, 2001, AIME.

Search for Better Students to Learn Distilled Knowledge pdf

Volker Tresp, Jindong Gu, Volker Tresp, 2020, ECAI.

Ieee Transactions on Knowledge and Data Engineering Probabilistic Memory-based Collaborative Filtering

Hans-Peter Kriegel, Anton Schwaighofer, Volker Tresp, 2022 .

Dirichlet Enhanced Latent Semantic Analysis

Volker Tresp, Shipeng Yu, Kai Yu, 2005, AISTATS.

Learning with Memory Embeddings pdf

Volker Tresp, Yinchong Yang, Denis Krompass, 2015, ArXiv.

Learning Gaussian Process Kernels via Hierarchical Bayes

Anton Schwaighofer, Volker Tresp, Kai Yu, 2004, NIPS.

A Logistic Additive Model for Relation Prediction in Multi-relational data.

Xueyan Jiang, Volker Tresp, Denis Krompass, 2013 .

The generalized Bayesian committee machine

Volker Tresp, Volker Tresp, 2000, KDD '00.

Videographic tomography. II. Reconstruction with fan-beam projection data

Volker Tresp, Arthur F. Gmitro, Rodney Snell, 1994, IEEE Trans. Medical Imaging.

Soft Clustering on Graphs

Volker Tresp, Shipeng Yu, Kai Yu, 2005, NIPS.

Graph Hawkes Network for Reasoning on Temporal Knowledge Graphs pdf

Stephan Günnemann, Zhen Han, Volker Tresp, 2020, ArXiv.

Heterogenous Data Fusion via a Probabilistic Latent-Variable Model

Volker Tresp, Kai Yu, Volker Tresp, 2004, ARCS.

Understanding Individual Decisions of CNNs via Contrastive Backpropagation

Volker Tresp, Yinchong Yang, Jindong Gu, 2018, ACCV.

Reducing the Rank in Relational Factorization Models by Including Observable Patterns

Xueyan Jiang, Volker Tresp, Maximilian Nickel, 2014, NIPS.

Walking the Tightrope: An Investigation of the Convolutional Autoencoder Bottleneck pdf

Volker Tresp, Ilja Manakov, Markus Rohm, 2019, ArXiv.

Hierarchical Bayesian Models for Collaborative Tagging Systems

Hans-Peter Kriegel, Achim Rettinger, Volker Tresp, 2009, 2009 Ninth IEEE International Conference on Data Mining.

Averaging, maximum penalized likelihood and Bayesian estimation for improving Gaussian mixture probability density estimates

Volker Tresp, Dirk Ormoneit, Volker Tresp, 1998, IEEE Trans. Neural Networks.

Scalable Relational Learning for Sparse and Incomplete Domains

Achim Rettinger, Volker Tresp, Markus Bundschus, 2009 .

Predicting the co-evolution of event and Knowledge Graphs

Volker Tresp, Yinchong Yang, Denis Krompass, 2015, 2016 19th International Conference on Information Fusion (FUSION).

Fraud detection in communication networks using neural and probabilistic methods

Volker Tresp, Michiaki Taniguchi, Jaakko Hollmén, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

Mean field inference in a general probabilistic setting

Volker Tresp, Reimar Hofmann, Michael Haft, 1999, AISTATS.

Extraction of semantic biomedical relations from text using conditional random fields

Hans-Peter Kriegel, Volker Tresp, Markus Bundschus, 2008, BMC Bioinformatics.

Core Technologies for the Internet of Services

Kawa Nazemi, Thomas Sporer, Volker Tresp, 2014, Towards the Internet of Services.

Combining Information Extraction, Deductive Reasoning and Machine Learning for Relation Prediction

Xueyan Jiang, Volker Tresp, Yi Huang, 2012, ESWC.

Towards BOTTARI: Using Stream Reasoning to Make Sense of Location-Based Micro-posts

Emanuele Della Valle, Seon-Ho Kim, Volker Tresp, 2011, ESWC Workshops.

A scalable approach for statistical learning in semantic graphs

Hans-Peter Kriegel, Achim Rettinger, Volker Tresp, 2014, Semantic Web.