C. Igel

C. Igel, 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

Structure optimization and isomorphisms

C. Igel, P. Stagge, 2001 .

A Unified View on Multi-class Support Vector Classification

Christian Igel, Ürün Dogan, Tobias Glasmachers, 2016, J. Mach. Learn. Res..

A No-Free-Lunch Theorem for Non-Uniform Distributions of Target Functions

Marc Toussaint, C. Igel, 2004 .

Improved step size adaptation for the MO-CMA-ES

Christian Igel, Thomas Voß, Nikolaus Hansen, 2010, GECCO '10.

Neural network structures and isomorphisms: random walk characteristics of the search space

C. Igel, P. Stagge, 2000, 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks. Proceedings of the First IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (Cat. No.00.

3 Modifications 3 . 1 A New Weight-Backtracking

C. Igel, Michael Hüsken, 2007 .

Fast training of multi-class support vector

C. Igel, 2018 .

Christian Igel Machine Learning : Kernel-based Methods

C. Igel, 2008 .

Christian Igel and Kumar Chellapilla

K. Chellapilla, C. Igel, 2007 .

The Multi-objective Variable Metric Evolution Strategy Part I

N. Hansen, C. Igel, Stefan Roth, 2005 .

91 'advances in Genetic Programming Iii, Research and Educational Use Only'

K. Chellapilla, C. Igel, 2022 .

Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry*

C. Igel, M. Nielsen, M. Lillholm, 2016, NeuroImage: Clinical.

Dementia Diagnosis using MRI Cortical Thickness , Shape , Texture , and Volumetry

C. Igel, M. Nielsen, M. Lillholm, 2014 .

Toward registration of 3D ultrasound and CT images of the spine in clinical praxis: design and evaluation of a data acquisition protocol.

C. Igel, K. Schmieder, I. Pechlivanis, 2009, Ultrasound in medicine & biology.

Early detection of Alzheimer's disease using MRI hippocampal texture

Lauge Sørensen, Egill Rostrup, Christian Igel, 2016, Human brain mapping.

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

Christina Lioma, Akshay Pai, Bulat Ibragimov, 2020, Scientific Reports.

Sacrificing information for the greater good: how to select photometric bands for optimal accuracy

Fabian Gieseke, Christian Igel, Kim Steenstrup Pedersen, 2015, Monthly Notices of the Royal Astronomical Society.

An unexpectedly large count of trees in the West African Sahara and Sahel

Martin Brandt, Johannes Schöning, Rasmus Fensholt, 2020, Nature.

Summary of Rechenberg's Analysis of Improvement Probability and Speed of Improvement

C. Igel, 1998 .

Fitness distributions: tools for designing efficient evolutionary computations

Christian Igel, Kumar Chellapilla, K. Chellapilla, 1999 .

Self-Supervised Speech Representation Learning: A Review

Jakob Drachmann Havtorn, Abdel-rahman Mohamed, T. Sainath, 2022, 2205.10643.

A multi-institute automated segmentation evaluation on a standard dataset: Findings from the international workshop on osteoarthritis imaging segmentation challenge

Mehmet Akcakaya, Drew A. Torigian, Akshay Pai, 2020 .

Self-Supervised Speech Representation Learning: A Review

Jakob Drachmann Havtorn, Abdel-rahman Mohamed, T. Sainath, 2022, ArXiv.

Hippocampal texture predicts conversion from MCI to Alzheimer’s disease

Lauge Sørensen, Christian Igel, Mads Nielsen, 2013, Alzheimer's & Dementia.

Evolutionary Kernel Learning

Christian Igel, C. Igel, 2017, Encyclopedia of Machine Learning and Data Mining.

Data, Knowledge, and Computation

Christian Igel, C. Igel, 2021, KI - Künstliche Intelligenz.

Proposal for IJCNN 2013 competition: The German Traffic Sign Detection Benchmark

Johannes Stallkamp, Marc Schlipsing, Jan Salmen, 2013 .

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

Christian Igel, Rasmus Kær Jørgensen, C. Igel, 2021, Intell. Syst. Account. Finance Manag..

Toward an automated dynamic organization )

Bernd Bischl, Günter Rudolph, Rainer Martin, 2011 .

Resilient Backpropagation (Rprop) for Batch-learning in TensorFlow

Christian Igel, Ciprian Florescu, C. Igel, 2018, ICLR.

Automatic Galaxy Classification via Machine Learning Techniques: Parallelized Rotation/Flipping INvariant Kohonen Maps (PINK)

Christian Igel, Fabian Gieseke, Christian Igel, 2015 .

GECCO ’14: Proceedings of the 2014 conference on Genetic and evolutionary computation

Julian Togelius, Christine Zarges, Hitoshi Iba, 2014 .

Explanation

Subbarao Kambhampati, Krzysztof Krawiec, Moshe Sipper, 1953, Cladistics : the international journal of the Willi Hennig Society.

CrossCohort Automatic Knee MRI Segmentation With MultiPlanar UNets

C. Igel, A. Pai, E. Dam, 2022 .

Impact of device programming on the success of the first anti-tachycardia pacing therapy: An anonymized large-scale study

C. Igel, S. Shakibfar, Oswin Krause, 2019, PloS one.

Energy Consumption-Aware Tabular Benchmarks for Neural Architecture Search

C. Igel, Raghavendra Selvan, Pedram Bakhtiarifard, 2022, ArXiv.

Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods

C. Igel, F. Gieseke, T. Friborg, 2022, Remote. Sens..

Self-Supervised Speech Representation Learning: A Review

Tara N. Sainath, Jakob Drachmann Havtorn, Abdel-rahman Mohamed, 2022, IEEE Journal of Selected Topics in Signal Processing.

Universitet Big universe , big data

K. S. Pedersen, C. Igel, F. Gieseke, 2018 .

Big universe, big data

C. Igel, F. Gieseke, Kristoffer Stensbo-Smidt, 2017 .

Linear feature selection in texture analysis - A PLS based method

C. Igel, M. Lillholm, E. Dam, 2013, Machine Vision and Applications.

Allometric equations to estimate the dry mass of Sahel woody plants mapped with very-high resolution satellite imagery

C. Igel, J. Chave, P. Hiernaux, 2023, Forest Ecology and Management.

LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing

Zhenming Peng, C. Igel, F. Gieseke, 2022, 2022 IEEE 8th International Conference on Computer and Communications (ICCC).

Reinforcement learning in a nutshell

Christian Igel, Martin A. Riedmiller, Verena Heidrich-Meisner, 2007, ESANN.

Neutrality and self-adaptation

Marc Toussaint, Christian Igel, Marc Toussaint, 2003, Natural Computing.

Operator adaptation in evolutionary computation and its application to structure optimization of neural networks

Christian Igel, Martin Kreutz, C. Igel, 2003, Neurocomputing.

A Dynamic Neural Field Model of Mesoscopic Cortical Activity Captured with Voltage-Sensitive Dye Imaging

Christian Igel, Amiram Grinvald, Dirk Jancke, 2010, PLoS Comput. Biol..

Active learning with support vector machines

Christian Igel, Kim Steenstrup Pedersen, Jan Kremer, 2014, WIREs Data Mining Knowl. Discov..

Cross‐Cohort Automatic Knee MRI Segmentation With Multi‐Planar U‐Nets

C. Igel, A. Pai, E. Dam, 2021, Journal of magnetic resonance imaging : JMRI.

U-Sleep: resilient high-frequency sleep staging

C. Igel, P. Jennum, M. Nikolic, 2021, npj Digital Medicine.

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging pdf

Christian Igel, Mathias Perslev, Sune Darkner, 2019, NeurIPS.

One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation

Akshay Pai, Christian Igel, Mathias Perslev, 2019, MICCAI.

Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote

C. Igel, Yevgeny Seldin, A. Masegosa, 2021, NeurIPS.

Evolutionary Optimization of Neural Systems: The Use of Strategy Adaptation

Christian Igel, Frauke Friedrichs, Stefan Wiegand, 2005 .

Neuroevolution for reinforcement learning using evolution strategies

Christian Igel, C. Igel, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

Evolutionary tuning of multiple SVM parameters

Christian Igel, Frauke Friedrichs, C. Igel, 2005, ESANN.

Evaluation Data

Joshua D. Knowles, S. Kambhampati, T. Heskes, 2010, Encyclopedia of Machine Learning.

An Introduction to Restricted Boltzmann Machines

Christian Igel, Asja Fischer, Asja Fischer, 2012, CIARP.

Computational Complexity of Linear Large Margin Classification With Ramp Loss

Christian Igel, Søren Frejstrup Maibing, C. Igel, 2015, AISTATS.

Protein fold class prediction using neural networks with tailored early-stopping

J. Gebert, C. Igel, T. Wiebringhaus, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies

Christian Igel, Nikolaus Hansen, Thorsten Suttorp, 2006, GECCO.

Efficient covariance matrix update for variable metric evolution strategies

Christian Igel, Nikolaus Hansen, Thorsten Suttorp, 2009, Machine Learning.

Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy

Christian Igel, Fabian Gieseke, Kim Steenstrup Pedersen, 2017, IEEE Intelligent Systems.

Derandomized Evolution Strategies in Computational Neuroscience

Christian Igel, Hubert R. Dinse, Marc Nunkesser, 2007 .

Evolutionary Adaptation of Nonlinear Dynamical Systems in Computational Neuroscience

Christian Igel, Hubert R. Dinse, Christian Klaes, 2004, Genetic Programming and Evolvable Machines.

A Brief Overview of Unsupervised Neural Speech Representation Learning

Jakob Drachmann Havtorn, C. Igel, Lars Maaløe, 2022, ArXiv.

Hydroacoustic Signal Classification Using Support Vector Machines

Christian Igel, Mark K. Prior, Matthias Tuma, 2012 .

Fast Training of Multi-Class Support Vector Machines

Christian Igel, Tobias Glasmachers, Urun Dogan, 2011 .

On Classes of Functions for which No Free Lunch Results Hold

Marc Toussaint, Christian Igel, Marc Toussaint, 2001, Inf. Process. Lett..

Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition

Johannes Stallkamp, Marc Schlipsing, Jan Salmen, 2012, Neural Networks.

Automatic FDG-PET-based tumor and metastatic lymph node segmentation in cervical cancer

Christian Igel, Sune Darkner, Henrik G. Jensen, 2014, Medical Imaging.

Training restricted Boltzmann machines: An introduction

Christian Igel, Asja Fischer, Asja Fischer, 2014, Pattern Recognit..

Uncertainty handling CMA-ES for reinforcement learning

Christian Igel, Verena Heidrich-Meisner, C. Igel, 2009, GECCO.

Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem

Christian Igel, Verena Heidrich-Meisner, C. Igel, 2008, EWRL.

Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning

C. Igel, J. Svendsen, S. Shakibfar, 2018, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

OP-EUPA180260 268..274

C. Igel, J. Svendsen, S. Shakibfar, 2019 .

Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda

C. Tucker, C. Igel, D. Skole, 2022, Nature Climate Change.

Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement

Bo Markussen, Gregor Schöner, Lars Lau Raket, 2016, PLoS Comput. Biol..

The logarithmic hypervolume indicator

Tobias Friedrich, Christian Igel, Karl Bringmann, 2011, FOGA '11.

Lecture Notes on Constraint Convex Optimization

C. Igel, 2009 .

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset pdf

Mehmet Akcakaya, Akshay Pai, Ulas Bagci, 2020, Radiology. Artificial intelligence.

Deep learning based 3D point cloud regression for estimating forest biomass

C. Igel, F. Gieseke, Katerina Trepekli, 2021, SIGSPATIAL/GIS.

Evolutionary Computing

Thomas E. Potok, Joshua D. Knowles, Robert M. Patton, 2019, Encyclopedia of Machine Learning and Data Mining.

Uncertainty Handling in Model Selection for Support Vector Machines

Christian Igel, Tobias Glasmachers, T. Glasmachers, 2008, PPSN.

Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite

Oswin Krause, Christian Igel, Nikolaus Hansen, 2016, GECCO.

Scaling up indicator-based MOEAs by approximating the least hypervolume contributor: a preliminary study

Tobias Friedrich, Christian Igel, Karl Bringmann, 2010, GECCO '10.

Speeding up many-objective optimization by Monte Carlo approximations

Tobias Friedrich, Christian Igel, Karl Bringmann, 2013, Artif. Intell..

Multi-Objective Optimization of Support Vector Machines

Christian Igel, Thorsten Suttorp, C. Igel, 2006, Multi-Objective Machine Learning.

Multi-objective Model Selection for Support Vector Machines

Christian Igel, C. Igel, 2005, EMO.

Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract)

Oswin Krause, Christian Igel, Asja Fischer, 2020, IJCAI.

Towards exaggerated emphysema stereotypes

Lauge Sørensen, Marleen de Bruijne, Christian Igel, 2012, Medical Imaging.

New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization

Heike Trautmann, Christian Igel, Thomas Voß, 2010, PPSN.

Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

Andreas D. Lauritzen, Abraham George Smith, Marleen de Bruijne, 2021, Scientific reports.

Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database

Christian Igel, Wolfgang Banzhaf, Jens Niehaus, 2007, Evolutionary Computation.

Remember to Correct the Bias When Using Deep Learning for Regression!

C. Igel, Stefan Oehmcke, 2022, KI - Künstliche Intelligenz.

Evolutionary kernel machines

Oliver Kramer, Günter Rudolph, Christian Igel, 2012, Evol. Intell..

Adaptive pattern recognition in real-time video-based soccer analysis

Marc Schlipsing, Jan Salmen, Christian Igel, 2017, Journal of Real-Time Image Processing.

Towards Automatic Cartilage Quantification in Clinical Trials – Continuing from the 2019 IWOAI Knee Segmentation Challenge

Arjun D Desai, C. Igel, B. Hargreaves, 2023, Osteoarthritis Imaging.

CMA-ES with Optimal Covariance Update and Storage Complexity

Oswin Krause, Christian Igel, Dídac Rodríguez Arbonès, 2016, NIPS.

A Note on Generalization Loss When Evolving Adaptive Pattern Recognition Systems

Christian Igel, C. Igel, 2013, IEEE Transactions on Evolutionary Computation.

Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts

Christian Igel, Peter Meinicke, Tobias Glasmachers, 2006, ICANN.

Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network

Christian Igel, Mads Nielsen, François Lauze, 2013, MICCAI.

Detection of traffic signs in real-world images: The German traffic sign detection benchmark

Johannes Stallkamp, Marc Schlipsing, Jan Salmen, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Mask-FPAN: Semi-Supervised Face Parsing in the Wild With De-Occlusion and UV GAN

C. Igel, F. Gieseke, Lei Li, 2022, ArXiv.

BuildSeg: A General Framework for the Segmentation of Buildings

C. Igel, F. Gieseke, Lei Li, 2023, Nordic Machine Intelligence.

On Scaling Contrastive Representations for Low-Resource Speech Recognition

Christian Igel, Lars Maaloe, Jakob Drachmann Havtorn, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

German Traffic Sign Detection Benchmark (GTSDB)

Christian Igel, C. Igel, 2019 .

Huge Music Archives on Mobile Devices

Bernd Bischl, Günter Rudolph, Rainer Martin, 2011, IEEE Signal Processing Magazine.

Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters

Christian Igel, Tobias Glasmachers, T. Glasmachers, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Registration of CT and Intraoperative 3-D Ultrasound Images of the Spine Using Evolutionary and Gradient-Based Methods

Kirsten Schmieder, Christian Igel, Susanne Winter, 2008, IEEE Transactions on Evolutionary Computation.

A Strongly Quasiconvex PAC-Bayesian Bound

Christian Igel, Yevgeny Seldin, Olivier Wintenberger, 2016, ALT.

Genesis of Organic Computing Systems: Coupling Evolution and Learning

Bernhard Sendhoff, Christian Igel, B. Sendhoff, 2008, Organic Computing.

Chaining Syllogism Applied to Fuzzy IF-THEN Rules and Rule Bases

Karl-Heinz Temme, Christian Igel, C. Igel, 1997, Fuzzy Days.

Synergies between Evolutionary and Neural Computation

Bernhard Sendhoff, Christian Igel, B. Sendhoff, 2005, ESANN.

Evolutionary Multi-Objective Optimisation Of Neural Networks For Face Detection

Christian Igel, Uwe Handmann, Stefan Wiegand, 2004, Int. J. Comput. Intell. Appl..

No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics

Christian Igel, C. Igel, 2014, Theory and Principled Methods for the Design of Metaheuristics.

Multi-Objective Neural Network Optimization for Visual Object Detection

Stefan Roth, Christian Igel, Alexander Rainer Tassilo Gepperth, 2006, Multi-Objective Machine Learning.

Second Order PAC-Bayesian Bounds for the Weighted Majority Vote pdf

Christian Igel, Yevgeny Seldin, Andr'es R. Masegosa, 2020, NeurIPS.

High-School Dropout Prediction Using Machine Learning: A Danish Large-scale Study.

Stephen Alstrup, Christian Igel, C. Igel, 2015 .

Automatic Motility Analysis of Human Sperm

Malte Stær Nissen, C. Igel, S. Kjærulff, 2018 .

Shape Index Descriptors Applied to Texture-Based Galaxy Analysis

Christian Igel, Kim Steenstrup Pedersen, K. S. Pedersen, 2013, ICCV.

Recycling on a Cosmic Scale – Extracting New Information from Old Data Sets

K. S. Pedersen, C. Igel, F. Gieseke, 2016 .

Towards more comprehensive nationwide familial aggregation studies in Denmark: The Danish Civil Registration System versus the lite Danish Multi-Generation Register.

C. Igel, P. Mortensen, Anders Søgaard, 2023, Scandinavian journal of public health.

More than one quarter of Africa ’ s tree cover is found outside areas previously classi ﬁ ed as forest

C. Tucker, C. Igel, D. Skole, 2023 .

Graph isomorphisms effect on structure optimization of neural networks

Christian Igel, C. Igel, P. Stagge, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Neutrality: a necessity for self-adaptation

Marc Toussaint, Christian Igel, Marc Toussaint, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

Effects of phenotypic redundancy in structure optimization

Christian Igel, Peter Stagge, C. Igel, 2002, IEEE Trans. Evol. Comput..

Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale

C. Igel, F. Gieseke, R. Fensholt, 2023, PNAS nexus.

On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions pdf

Christian Igel, Asja Fischer, Kai Brügge, 2020, AISTATS.

Algorithms for estimating the partition function of restricted Boltzmann machines

Oswin Krause, Christian Igel, Asja Fischer, 2020, Artif. Intell..

Sub-continental-scale carbon stocks of individual trees in African drylands

Scott S. Sinno, C. Tucker, C. Igel, 2023, Nature.

Smooth Monotonic Networks

C. Igel, 2023, arXiv.org.

Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets

Christian Igel, Mark Prior, Matthias Tuma, 2010, 2010 20th International Conference on Pattern Recognition.

Are Multilingual Sentiment Models Equally Right for the Right Reasons?

C. Igel, Anders Søgaard, Fiammetta Caccavale, 2022, BLACKBOXNLP.

Kremer Active and Adaptive Learning from Biased Data with Applications in Astronomy

C. Igel, Jan Kremer, 2016 .

Allometric Equations to Estimate the Dry Mass of Sahel Woody Plants from Very-High Resolution Satellite Imagery

C. Igel, J. Chave, P. Hiernaux, 2022, SSRN Electronic Journal.

Approximation properties of DBNs with binary hidden units and real-valued visible units

Oswin Krause, Christian Igel, Asja Fischer, 2013, ICML.

The chaining syllogism in fuzzy logic

Karl-Heinz Temme, Christian Igel, C. Igel, 2004, IEEE Transactions on Fuzzy Systems.

Smooth Monotonic Networks

C. Igel, 2023, ArXiv.

A More Efficient Rank-one Covariance Matrix Update for Evolution Strategies

Oswin Krause, Christian Igel, C. Igel, 2015, FOGA.

Information Bottleneck: Exact Analysis of (Quantized) Neural Networks

C. Igel, M. Nielsen, S. Lorenzen, 2021, ICLR.

(QUANTIZED) NEURAL NETWORKS

C. Igel, Mads, Stephan Sloth, 2022 .

High-school dropout prediction using machine learning

Stephen Alstrup, Christian Igel, C. Igel, 2018 .

A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model

C. Igel, Oswin Krause, Steffen Czolbe, 2020, NeurIPS.

MultiFin: A Dataset for Multilingual Financial NLP

C. Igel, Xiang Dai, Desmond Elliott, 2023, FINDINGS.

Second-Order SMO Improves SVM Online and Active Learning

Christian Igel, Tobias Glasmachers, T. Glasmachers, 2008, Neural Computation.

Robust Active Label Correction

Christian Igel, Fei Sha, Jan Kremer, 2018, AISTATS.

Task-dependent evolution of modularity in neural networks

Marc Toussaint, Christian Igel, Michael Hüsken, 2002 .

Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring

Christian Igel, Mark Prior, Matthias Tuma, 2016, IEEE Transactions on Geoscience and Remote Sensing.

Sparse Incomplete LU-Decomposition for Wave Farm Designs Under Realistic Conditions

Markus Wagner, Oswin Krause, Christian Igel, 2018, PPSN.

Do End-to-End Speech Recognition Models Care About Context?

Christian Igel, Anders Søgaard, Jakob Drachmann Havtorn, 2020, INTERSPEECH.

bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices

Fabian Gieseke, Christian Igel, Cosmin E. Oancea, 2017, Knowl. Based Syst..

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search

C. Igel, Raghavendra Selvan, Pedram Bakhtiarifard, 2022, 2210.06015.

More than one quarter of Africa’s tree cover is found outside areas previously classified as forest

C. Tucker, C. Igel, D. Skole, 2023, Nature communications.

Bi-modal Variational Autoencoders for Metabolite Identification Using Tandem Mass Spectrometry

C. Igel, D. McCloskey, S. Kutuzova, 2021, bioRxiv.

Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts pdf

Oswin Krause, Christian Igel, Mads Nielsen, 2021, ArXiv.

Label-similarity Curriculum Learning

Christian Igel, Ürün Dogan, Aniket Anand Deshmukh, 2019, ECCV.

Cross-reactive metal ion sensor array in a micro titer plate format.

Christian Igel, Ingo Klimant, Gregor Liebsch, 2003, Analytical chemistry.

Training Big Random Forests with Little Resources

Fabian Gieseke, Christian Igel, C. Igel, 2018, KDD.

Mask-FPAN: Semi-Supervised Face Parsing in the Wild With De-Occlusion and UV GAN

C. Igel, F. Gieseke, Lei Li, 2022, Comput. Graph..

Structure optimization of reservoir networks

Christian Igel, Benjamin Roeschies, C. Igel, 2010, Log. J. IGPL.

Towards exaggerated image stereotypes

Chen Chen, Christian Igel, Mads Nielsen, 2011, The First Asian Conference on Pattern Recognition.

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs

Fabian Gieseke, Christian Igel, Justin Heinermann, 2014, ICML.

Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI

C. Igel, Raghavendra Selvan, Dustin Wright, 2023, ArXiv.

Explanation

Shiau Hong Lim, S. Kambhampati, T. Heskes, 1953, Cladistics : the international journal of the Willi Hennig Society.

Femoral cartilage segmentation in Knee MRI scans using two stage voxel classification

Christian Igel, Mads Nielsen, François Lauze, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage

Christian Igel, Mads Nielsen, François Lauze, 2012, Medical Imaging.

PAC-Bayesian Aggregation without Cross-Validation

C. Igel, Yevgeny Seldin, Niklas Thiemann, 2016, ArXiv.

Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search

C. Igel, V. Heidrich-Meisner, 2009, ICML '09.

The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe.

C. Igel, R. Fensholt, J. Chave, 2023, Science advances.

Nearest neighbor density ratio estimation for large-scale applications in astronomy

Fabian Gieseke, Christian Igel, K. S. Pedersen, 2015, Astron. Comput..

Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition

C. Igel, J. Stallkamp, Marc Schlipsing, 2012, Neural Networks.