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M. Besserve · SciRah

Researcher profile · Semantic Scholar

M. Besserve

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M. Besserve — researcher profile on SciRah

h-index: 17
Works: 54
Citations: 1,482

Most-cited papers

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel +3 more
2021Neural Information Processing Systems432 citations
Semantic Scholar
Independent mechanism analysis, a new concept?
Luigi Gresele, Julius von Kügelgen, Vincent Stimper, B. Schölkopf +1 more
2021Neural Information Processing Systems135 citations
Semantic Scholar
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen, M. Besserve, Wendong Liang, Luigi Gresele +4 more
2023Neural Information Processing Systems130 citations Open access
Semantic Scholar
Classification methods for ongoing EEG and MEG signals.
M. Besserve, K. Jerbi, F. Laurent, Sylvain Baillet +2 more
2007Biological Research105 citations Open access
Semantic Scholar
Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis
M. Besserve, B. Schölkopf, N. Logothetis, S. Panzeri
2010Journal of Computational Neuroscience77 citations Open access
Semantic Scholar
Multimodal information improves the rapid detection of mental fatigue
F. Laurent, M. Valderrama, M. Besserve, M. Guillard +3 more
2013Biomedical Signal Processing and Control68 citations
Semantic Scholar
Causal Component Analysis
Wendong Liang, Armin Keki'c, Julius von Kügelgen, Simon Buchholz +3 more
2023Neural Information Processing Systems65 citations Open access
Semantic Scholar
Function Classes for Identifiable Nonlinear Independent Component Analysis
Simon Buchholz, M. Besserve, B. Schölkopf
2022Neural Information Processing Systems65 citations Open access
Semantic Scholar
Telling cause from effect in deterministic linear dynamical systems
Naji Shajarisales, D. Janzing, B. Schölkopf, M. Besserve
2015International Conference on Machine Learning53 citations
Semantic Scholar
Improving quantification of functional networks with EEG inverse problem: Evidence from a decoding point of view
M. Besserve, J. Martinerie, L. Garnero
2011NeuroImage48 citations
Semantic Scholar
Prediction of performance level during a cognitive task from ongoing EEG oscillatory activities.
M. Besserve, M. Philippe, G. Florence, F. Laurent +2 more
2008Clinical Neurophysiology37 citations
Semantic Scholar
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
P. Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen +5 more
2022Neural Information Processing Systems35 citations Open access
Semantic Scholar
Discrepancies between Multi-Electrode LFP and CSD Phase-Patterns: A Forward Modeling Study
R. Hindriks, X. Arsiwalla, T. Panagiotaropoulos, M. Besserve +3 more
2016Front. Neural Circuits29 citations Open access
Semantic Scholar
Exploring the Latent Space of Autoencoders with Interventional Assays
Felix Leeb, Stefan Bauer, M. Besserve, B. Schölkopf
2021Neural Information Processing Systems26 citations Open access
Semantic Scholar
Homomorphism Autoencoder - Learning Group Structured Representations from Observed Transitions
Hamza Keurti, Hsiao-Ru Pan, M. Besserve, B. Grewe +1 more
2022International Conference on Machine Learning25 citations Open access
Semantic Scholar
Targeted Reduction of Causal Models
Armin Keki'c, B. Schölkopf, M. Besserve
2023Conference on Uncertainty in Artificial Intelligence21 citations
Semantic Scholar
Causal Feature Selection via Orthogonal Search
Anant Raj, Stefan Bauer, Ashkan Soleymani, M. Besserve +1 more
2020Trans. Mach. Learn. Res.20 citations
Semantic Scholar
Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators
M. Besserve, N. Logothetis, B. Schölkopf
2013Neural Information Processing Systems14 citations
Semantic Scholar
Towards a learning-theoretic analysis of spike-timing dependent plasticity
David Balduzzi, M. Besserve
2012Neural Information Processing Systems10 citations
Semantic Scholar
Structure by Architecture: Disentangled Representations without Regularization
Felix Leeb, Guilia Lanzillotta, Yashas Annadani, M. Besserve +2 more
20219 citations
Semantic Scholar
Structure by Architecture: Structured Representations without Regularization
Felix Leeb, Giulia Lanzillotta, Yashas Annadani, M. Besserve +2 more
2020International Conference on Learning Representations9 citations
Semantic Scholar
From Univariate to Multivariate Coupling Between Continuous Signals and Point Processes: A Mathematical Framework
Shervin Safavi, N. Logothetis, M. Besserve
2020Neural Computation9 citations Open access
Semantic Scholar
Metabolic Cost as an Organizing Principle for Cooperative Learning
David Balduzzi, Pedro A. Ortega, M. Besserve
2012Advances in Complex Systems9 citations Open access
Semantic Scholar
Non-invasive classification of cortical activities for brain computer interface: A variable selection approach
M. Besserve, J. Martinerie, L. Garnero
2008IEEE International Symposium on Biomedical Imaging9 citations
Semantic Scholar
Independent Mechanism Analysis and the Manifold Hypothesis
Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, M. Besserve +1 more
2023arXiv.org6 citations
Semantic Scholar
Learning soft interventions in complex equilibrium systems
M. Besserve, B. Schölkopf
2021Conference on Uncertainty in Artificial Intelligence5 citations
Semantic Scholar
Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations
M. Besserve, Naji Shajarisales, D. Janzing, B. Schölkopf
2021CLEaR5 citations
Semantic Scholar
Causal learning with sufficient statistics: an information bottleneck approach
D. Chicharro, M. Besserve, S. Panzeri
2020arXiv.org5 citations
Semantic Scholar
Assaying Large-scale Testing Models to Interpret Covid-19 Case Numbers. A Cross-country Study
M. Besserve, Simon Buchholz, B. Schölkopf
20204 citations
Semantic Scholar
Intrinsic disentanglement: an invariance view for deep generative models
M. Besserve, Rémy Sun, B. Schölkopf
2018International Conference on Machine Learning4 citations
Semantic Scholar
Towards Robust and Specific Causal Discovery from fMRI
Kun Zhang, Biwei Huang, B. Schölkopf, M. Besserve +2 more
2015arXiv.org4 citations
Semantic Scholar
Homomorphism Autoencoder — Learning Group Structured Representations from Interactions
Hamza Keurti, Hsiao-Ru Pan, M. Besserve, B. Grewe +1 more
20222 citations
Semantic Scholar
A central limit like theorem for Fourier sums
D. Janzing, Naji Shajarisales, M. Besserve
20172 citations
Semantic Scholar
Finding dependencies between frequencies with the kernel cross-spectral density
M. Besserve, D. Janzing, N. Logothetis, B. Schölkopf
2011IEEE International Conference on Acoustics, Speech, and Signal Processing2 citations
Semantic Scholar
Unsupervised Causal Abstraction
Yuchen Zhu, Sergio Hernán, G. Mejía, B. Schölkopf +1 more
2 citations
Semantic Scholar
Linear Independent Component Analysis via Optimal Transport
Ashutosh Jha, M. Besserve, Simon Buchholz
2026arXiv.org1 citations
Semantic Scholar
Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies
Armin Keki'c, Jan Schneider, Dieter Büchler, B. Schölkopf +1 more
2025arXiv.org1 citations
Semantic Scholar
On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective"
Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, M. Besserve +1 more
2022arXiv.org1 citations
Semantic Scholar
Tinkering with black boxes: counterfactuals uncover modularity in generative models
M. Besserve, Rémy Sun, B. Schoelkopf
20181 citations
Semantic Scholar
Source Reconstruction and Synchrony Measurements for Revealing Functional Brain Networks and Classifying Mental States
F. Laurent, M. Besserve, L. Garnero, M. Philippe +2 more
2010International Journal of Bifurcation and Chaos in Applied Sciences and Engineering1 citations
Semantic Scholar
Reconstructing the cortical functional network during imagery tasks for boosting asynchronous BCI
M. Besserve, J. Martinerie, L. Garnero
20081 citations
Semantic Scholar
Prediction of cognitive states using MEG and Blind Source Separation
M. Besserve, K. Jerbi, L. Garnero, J. Martinerie
20071 citations
Semantic Scholar
Controlling for discrete unmeasured confounding in nonlinear causal models
Patrick Burauel, Frederick Eberhardt, M. Besserve
2024CLEaR0 citations
Semantic Scholar
Orthogonal Structure Search for Efficient Causal Discovery from Observational Data
Anant Raj, Luigi Gresele, M. Besserve, B. Schölkopf +1 more
2019arXiv.org0 citations
Semantic Scholar
Machine Learning and Neuroscience: Part 2
M. Besserve
20190 citations
Semantic Scholar
Neural mass modeling of the Ponto-Geniculo-Occipital wave and its neuromodulation
K. Shao, Nk Logothetis, M. Besserve
20190 citations
Semantic Scholar
Machine Learning and Neuroscience
M. Besserve
20190 citations
Semantic Scholar
Coordination via predictive assistants from a game-theoretic view
Philipp Geiger, Justus Winkelmann, Claudius Proissl, M. Besserve +1 more
2018arXiv.org0 citations
Semantic Scholar
On the difference between building and extracting patterns: a causal analysis of deep generative models.
M. Besserve, D. Janzing, B. Schoelkopf
20180 citations
Semantic Scholar
Coordination via predictive assistants: time series algorithms and game-theoretic analysis
Philipp Geiger, M. Besserve, Justus Winkelmann, Claudius Proissl +1 more
20180 citations
Semantic Scholar

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