Klaus-Robert Müller

116 publications

18 venues

H Index 46

Affiliation

Technical University of Berlin, Germany

Links

Name Venue Year citations
Set Learning for Accurate and Calibrated Models. ICLR 2024 0
Diffeomorphic Counterfactuals With Generative Models. TPAMI 2024 0
Relevant Walk Search for Explaining Graph Neural Networks. ICML 2023 0
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. CVPR 2023 0
Physics-Informed Bayesian Optimization of Variational Quantum Circuits. NIPS/NeurIPS 2023 0
XAI for Transformers: Better Explanations through Conservative Propagation. ICML 2022 10
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing. ICML 2022 0
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems. NIPS/NeurIPS 2022 1
Scrutinizing XAI using linear ground-truth data with suppressor variables. MLJ 2022 0
Higher-Order Explanations of Graph Neural Networks via Relevant Walks. TPAMI 2022 0
Building and Interpreting Deep Similarity Models. TPAMI 2022 0
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities. NIPS/NeurIPS 2021 28
Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging. NIPS/NeurIPS 2021 3
Explainable Deep One-Class Classification. ICLR 2021 0
Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance. AAAI 2020 2
Fairwashing explanations with off-manifold detergent. ICML 2020 48
Deep Semi-Supervised Anomaly Detection. ICLR 2020 0
Explanations can be manipulated and geometry is to blame. NIPS/NeurIPS 2019 203
N-ary decomposition for multi-class classification. MLJ 2019 27
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication. IJCNN 2019 0
Entropy-Constrained Training of Deep Neural Networks. IJCNN 2019 0
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs. AISTATS 2019 0
iNNvestigate Neural Networks! JMLR 2019 0
Curly: An AI-based Curling Robot Successfully Competing in the Olympic Discipline of Curling. IJCAI 2018 7
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions. NIPS/NeurIPS 2017 567
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. JMLR 2017 80
Minimizing Trust Leaks for Robust Sybil Detection. ICML 2017 9
An Empirical Study on The Properties of Random Bases for Kernel Methods. NIPS/NeurIPS 2017 13
The LRP Toolbox for Artificial Neural Networks. JMLR 2016 3
Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. ICANN 2016 265
Wasserstein Training of Restricted Boltzmann Machines. NIPS/NeurIPS 2016 98
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. CVPR 2016 0
Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms. ECML/PKDD 2015 15
Learning and Evaluation in Presence of Non-i.i.d. Label Noise. AISTATS 2014 18
Covariance shrinkage for autocorrelated data. NIPS/NeurIPS 2014 20
Generalizing Analytic Shrinkage for Arbitrary Covariance Structures. NIPS/NeurIPS 2013 17
Robust Spatial Filtering with Beta Divergence. NIPS/NeurIPS 2013 47
Learning Invariant Representations of Molecules for Atomization Energy Prediction. NIPS/NeurIPS 2012 116
Deep Boltzmann Machines as Feed-Forward Hierarchies. AISTATS 2012 18
Algebraic Geometric Comparison of Probability Distributions. JMLR 2012 0
Regression for sets of polynomial equations. AISTATS 2012 0
The Stationary Subspace Analysis Toolbox. JMLR 2011 17
Kernel Analysis of Deep Networks. JMLR 2011 115
ℓ ICANN 2011 0
Approximate Tree Kernels. JMLR 2010 0
Layer-wise analysis of deep networks with Gaussian kernels. NIPS/NeurIPS 2010 25
Temporal kernel CCA and its application in multimodal neuronal data analysis. MLJ 2010 99
How to Explain Individual Classification Decisions. JMLR 2010 0
Efficient and Accurate Lp-Norm Multiple Kernel Learning. NIPS/NeurIPS 2009 260
Subject independent EEG-based BCI decoding. NIPS/NeurIPS 2009 59
Playing Pinball with non-invasive BCI. NIPS/NeurIPS 2008 139
Estimating vector fields using sparse basis field expansions. NIPS/NeurIPS 2008 25
On Relevant Dimensions in Kernel Feature Spaces. JMLR 2008 131
Stopping conditions for exact computation of leave-one-out error in support vector machines. ICML 2008 5
Covariate Shift Adaptation by Importance Weighted Cross Validation. JMLR 2007 755
The Need for Open Source Software in Machine Learning. JMLR 2007 214
Optimal dyadic decision trees. MLJ 2007 54
Asymptotic Bayesian generalization error when training and test distributions are different. ICML 2007 31
Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing. NIPS/NeurIPS 2007 241
Machine Learning and Applications for Brain-Computer Interfacing. HCI 2007 27
Heterogeneous Component Analysis. NIPS/NeurIPS 2007 3
A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface. HCI 2007 112
Incremental Support Vector Learning: Analysis, Implementation and Applications. JMLR 2006 1
Inducing Metric Violations in Human Similarity Judgements. NIPS/NeurIPS 2006 12
Logistic Regression for Single Trial EEG Classification. NIPS/NeurIPS 2006 76
In Search of Non-Gaussian Components of a High-Dimensional Distribution. JMLR 2006 80
A Model Selection Method Based on Bound of Learning Coefficient. ICANN 2006 5
Denoising and Dimension Reduction in Feature Space. NIPS/NeurIPS 2006 16
Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach. NIPS/NeurIPS 2006 70
Model Selection Under Covariate Shift. ICANN 2005 30
Optimizing spatio-temporal filters for improving Brain-Computer Interfacing. NIPS/NeurIPS 2005 68
Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction. NIPS/NeurIPS 2005 5
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction. NIPS/NeurIPS 2005 14
Estimating Functions for Blind Separation When Sources Have Variance Dependencies. JMLR 2005 0
Feature Discovery in Non-Metric Pairwise Data. JMLR 2004 0
A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation. JMLR 2004 268
Regularizing generalization error estimators: a novel approach to robust model selection. ESANN 2004 0
Increase Information Transfer Rates in BCI by CSP Extension to Multi-class. NIPS/NeurIPS 2003 121
Feature Extraction for One-Class Classification. ICANN 2003 56
Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation. JMLR 2003 4
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. TPAMI 2003 221
Combining Features for BCI. NIPS/NeurIPS 2002 80
Clustering with the Fisher Score. NIPS/NeurIPS 2002 38
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification. TPAMI 2002 253
Selecting Ridge Parameters in Infinite Dimensional Hypothesis Spaces. ICANN 2002 2
New Methods for Splice Site Recognition. ICANN 2002 77
Going Metric: Denoising Pairwise Data. NIPS/NeurIPS 2002 75
Subspace information criterion for nonquadratic regularizers-Model selection for sparse regressors. IEEE Trans. Neural Networks 2002 12
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces. JMLR 2002 0
Estimating the Reliability of ICA Projections. NIPS/NeurIPS 2001 17
Soft Margins for AdaBoost. MLJ 2001 1313
Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers. ICANN 2001 35
Kernel Feature Spaces and Nonlinear Blind Souce Separation. NIPS/NeurIPS 2001 32
A New Discriminative Kernel From Probabilistic Models. NIPS/NeurIPS 2001 155
An introduction to kernel-based learning algorithms. IEEE Trans. Neural Networks 2001 3631
Classifying Single Trial EEG: Towards Brain Computer Interfacing. NIPS/NeurIPS 2001 531
Barrier Boosting. COLT 2000 41
A Mathematical Programming Approach to the Kernel Fisher Algorithm. NIPS/NeurIPS 2000 204
Robust Ensemble Learning for Data Mining. PAKDD 2000 24
Input space versus feature space in kernel-based methods. IEEE Trans. Neural Networks 1999 1261
Tools for computer-supported learning in organisations. HCI 1999 0
Unmixing Hyperspectral Data. NIPS/NeurIPS 1999 161
Hidden Markov gating for prediction of change points in switching dynamical systems. ESANN 1999 3
Invariant Feature Extraction and Classification in Kernel Spaces. NIPS/NeurIPS 1999 218
v-Arc: Ensemble Learning in the Presence of Outliers. NIPS/NeurIPS 1999 15
Kernel PCA and De-Noising in Feature Spaces. NIPS/NeurIPS 1998 1055
Regularizing AdaBoost. NIPS/NeurIPS 1998 54
Asymptotic statistical theory of overtraining and cross-validation. IEEE Trans. Neural Networks 1997 358
Analysis of Wake/Sleep EEG with Competing Experts. ICANN 1997 5
Kernel Principal Component Analysis. ICANN 1997 2288
Analysis of Drifting Dynamics with Neural Network Hidden Markov Models. NIPS/NeurIPS 1997 12
Predicting Time Series with Support Vector Machines. ICANN 1997 1018
Analysis of Drifting Dynamics with Competing Predictors. ICANN 1996 1
Prediction of Mixtures. ICANN 1996 6
Adaptive On-line Learning in Changing Environments. NIPS/NeurIPS 1996 87
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? NIPS/NeurIPS 1995 77
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