Klaus-Robert Müller
57 papers · 2002–2025 · 10 conferences · across top CS/AI conferences
Achievements
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🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (37) 🌈 Renaissance Researcher (8) 🐣 Hot Topic Early Bird
🌈
Renaissance Researcher
(8)
🌉
Interdisciplinary Bridge
🏃
Academic Marathon
(23)
🏠
Conference Loyalist
(25)
🌟
Keyword Trendsetter Combo
(8)
👑
Domain Dominant
(10)
🤝
Dynamic Duo
(13)
🌱
Topic Pioneer
🏆
Keyword Champion
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Grand Slam
🔬
Deep Specialist
(13)
🗃️
Keyword Collector
(150)
📈
Trend Setter
🔥
Unstoppable
(10)
🚀
Conference Pioneer
💎
Century Club
(57)
⚡
Prolific Year
(6)
Conferences
NIPS (25)
JMLR (17)
ICML (4)
AISTATS (3)
CVPR (2)
ICLR (2)
AAAI (1)
ACL (1)
IJCAI (1)
MICCAI (1)
Top co-authors
Research topics
Keywords
brain-computer interface
(6)
representation learning
(5)
layer-wise relevance propagation
(5)
signal processing
(4)
dimensionality reduction
(4)
neural network
(4)
model selection
(4)
feature extraction
(4)
kernel methods
(4)
transfer learning
(3)
common spatial patterns
(3)
feature attribution
(3)
support vector machine
(3)
electroencephalography
(3)
motor imagery
(3)
quantum chemistry
(3)
adversarial robustness
(2)
feature learning
(2)
time series
(2)
explainable ai
(2)
Papers
MeDi: Metadata-Guided Diffusion Models for Mitigating Biases in Tumor Classification
MICCAI 2025
xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology
NIPS 2024
MambaLRP: Explaining Selective State Space Sequence Models
NIPS 2024
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations
CVPR 2023
Physics-Informed Bayesian Optimization of Variational Quantum Circuits
NIPS 2023
XAI for Transformers: Better Explanations through Conservative Propagation
ICML 2022
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems
NIPS 2022
Efficient Computation of Higher-Order Subgraph Attribution via Message Passing
ICML 2022
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities
NIPS 2021
Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging
NIPS 2021
Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance
AAAI 2020
Fairwashing explanations with off-manifold detergent
ICML 2020
Deep Semi-Supervised Anomaly Detection
ICLR 2020
iNNvestigate Neural Networks!
JMLR 2019
Partial Optimality of Dual Decomposition for MAP Inference in Pairwise MRFs
AISTATS 2019
Explanations can be manipulated and geometry is to blame
NIPS 2019
Evaluating Recurrent Neural Network Explanations
ACL 2019
Learning how to explain neural networks: PatternNet and PatternAttribution
ICLR 2018
Curly: An AI-based Curling Robot Successfully Competing in the Olympic Discipline of Curling
IJCAI 2018
Minimizing Trust Leaks for Robust Sybil Detection
ICML 2017
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels
JMLR 2017
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
NIPS 2017
An Empirical Study on The Properties of Random Bases for Kernel Methods
NIPS 2017
Wasserstein Training of Restricted Boltzmann Machines
NIPS 2016
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks
CVPR 2016
The LRP Toolbox for Artificial Neural Networks
JMLR 2016
Covariance shrinkage for autocorrelated data
NIPS 2014
Robust Spatial Filtering with Beta Divergence
NIPS 2013
Generalizing Analytic Shrinkage for Arbitrary Covariance Structures
NIPS 2013
Learning Invariant Representations of Molecules for Atomization Energy Prediction
NIPS 2012
Algebraic Geometric Comparison of Probability Distributions
JMLR 2012
Regression for sets of polynomial equations
AISTATS 2012
Deep Boltzmann Machines as Feed-Forward Hierarchies
AISTATS 2012
Kernel Analysis of Deep Networks
JMLR 2011
The Stationary Subspace Analysis Toolbox
JMLR 2011
How to Explain Individual Classification Decisions
JMLR 2010
Layer-wise analysis of deep networks with Gaussian kernels
NIPS 2010
Approximate Tree Kernels
JMLR 2010
Subject independent EEG-based BCI decoding
NIPS 2009
Efficient and Accurate Lp-Norm Multiple Kernel Learning
NIPS 2009
Playing Pinball with non-invasive BCI
NIPS 2008
On Relevant Dimensions in Kernel Feature Spaces
JMLR 2008
Estimating vector fields using sparse basis field expansions
NIPS 2008
Covariate Shift Adaptation by Importance Weighted Cross Validation
JMLR 2007
The Need for Open Source Software in Machine Learning
JMLR 2007
Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing
NIPS 2007
Heterogeneous Component Analysis
NIPS 2007
Denoising and Dimension Reduction in Feature Space
NIPS 2006
In Search of Non-Gaussian Components of a High-Dimensional Distribution
JMLR 2006
Incremental Support Vector Learning: Analysis, Implementation and Applications
JMLR 2006
Logistic Regression for Single Trial EEG Classification
NIPS 2006
Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach
NIPS 2006
Inducing Metric Violations in Human Similarity Judgements
NIPS 2006
A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation
JMLR 2004
Feature Discovery in Non-Metric Pairwise Data
JMLR 2004
Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation
JMLR 2003
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
JMLR 2002