2024
Besserve, M., Safavi, S., Schölkopf, B., Logothetis, N.
LFP transient events in macaque subcortical areas reveal network coordination across scales and structures: a simultaneous fMRI-electrophysiology study
Computational and Systems Neuroscience Meeting (COSYNE), March 2024 (poster)
Shao, K., Xu, Y., Logothetis, N., Shen, Z., Besserve, M.
Koopman Spectral Analysis Uncovers the Temporal Structure of Spontaneous Neural Events
Computational and Systems Neuroscience Meeting (COSYNE), March 2024 (poster)
Ortu, F.
Interpreting How Large Language Models Handle Facts and Counterfactuals through Mechanistic Interpretability
University of Trieste, Italy, March 2024 (mastersthesis)
2023
Sakenyte, U.
Denoising Representation Learning for Causal Discovery
Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)
Kofler, A.
Efficient Sampling from Differentiable Matrix Elements
Technical University of Munich, Germany, September 2023 (mastersthesis)
Spieler, A. M.
Intrinsic complexity and mechanisms of expressivity of cortical neurons
University of Tübingen, Germany, March 2023 (mastersthesis)
Kladny, K.
CausalEffect Estimation by Combining Observational and Interventional Data
ETH Zurich, Switzerland, February 2023 (mastersthesis)
Qui, Z.
Towards Generative Machine Teaching
Technical University of Munich, Germany, February 2023 (mastersthesis)
Schneider, F.
ArchiSound: Audio Generation with Diffusion
ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)
Dittrich, A.
Generation and Quantification of Spin in Robot Table Tennis
University of Stuttgart, Germany, January 2023 (mastersthesis)
Jin, Z., Mihalcea, R.
Natural Language Processing for Policymaking
In Handbook of Computational Social Science for Policy, pages: 141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (inbook)
2022
Liang, W.
Investigating Independent Mechanisms in Neural Networks
Université Paris-Saclay, France, October 2022 (mastersthesis)
Keidar, D.
Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones
ETH Zurich, Switzerland, October 2022 (mastersthesis)
Schölkopf, B.
Causality, causal digital twins, and their applications
Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling (Dagstuhl Seminar 22382), (Editors: Berens, Philipp and Cranmer, Kyle and Lawrence, Neil D. and von Luxburg, Ulrike and Montgomery, Jessica), September 2022 (talk)
Feil, M.
Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning
Technnical University Munich, Germany, September 2022 (mastersthesis)
Sliwa, J.
Independent Mechanism Analysis for High Dimensions
University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)
Dominguez-Olmedo, R.
On the Adversarial Robustness of Causal Algorithmic Recourse
University of Tübingen, Germany, August 2022 (mastersthesis)
Ghosh, S.
Independent Mechanism Analysis in High-Dimensional Observation Spaces
ETH Zurich, Switzerland, June 2022 (mastersthesis)
Peters, J., Bauer, S., Pfister, N.
Causal Models for Dynamical Systems
In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)
Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I.
Towards Causal Algorithmic Recourse
In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)
Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z.
CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations
In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)
Schölkopf, B.
Causality for Machine Learning
In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (inbook)
2021
Scherrer, N.
Learning Neural Causal Models with Active Interventions
ETH Zurich, Switzerland, November 2021 (mastersthesis)
Bing, S.
HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness
ETH Zurich, Switzerland, October 2021 (mastersthesis)
Lanzillotta, G.
Study of the Interventional Consistency of Autoencoders
ETH Zurich, Switzerland, October 2021 (mastersthesis)
Mambelli, D.
Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning
ETH Zurich, Switzerland, October 2021 (mastersthesis)
Belousov, B., H., A., Klink, P., Parisi, S., Peters, J.
Reinforcement Learning Algorithms: Analysis and Applications
883, Studies in Computational Intelligence, Springer International Publishing, 2021 (book)
Scientific Report 2016 - 2021
2021 (mpi_year_book)
2020
Ahmed, O.
A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
ETH Zurich, Switzerland, October 2020 (mastersthesis)
DuMont Schütte, A.
A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging
ETH Zurich, Switzerland, October 2020 (mastersthesis)
Cacioppo, A.
Deep learning for the parameter estimation of tight-binding Hamiltonians
University of Roma, La Sapienza, Italy, May 2020 (mastersthesis)
Zecevic, M.
Learning Algorithms, Invariances, and the Real World
Technical University of Darmstadt, Germany, April 2020 (mastersthesis)
2019
Safavi, S., Logothetis, N., Besserve, M.
Multivariate coupling estimation between continuous signals and point processes
Neural Information Processing Systems 2019 - Workshop on Learning with Temporal Point Processes, December 2019 (talk)
Stimper, V.
Inferring the Band Structure from Band Mapping Data through Machine Learning
Technical University of Munich, September 2019 (mastersthesis)
Dietz, B.
Learning to Diagnose Diabetes from Magnetic Resonance Tomography
ETH Zurich, Switzerland, August 2019 (mastersthesis)
Meding, K., Schölkopf, B., Wichmann, F. A.
Perception of temporal dependencies in autoregressive motion
Perception, 48(2-suppl):141, 42nd European Conference on Visual Perception (ECVP), August 2019 (poster)
Bruijns, S. A., Meding, K., Schölkopf, B., Wichmann, F. A.
Phenomenal Causality and Sensory Realism
Perception, 48(2-suppl):141, 42nd European Conference on Visual Perception (ECVP), August 2019 (poster)
Shao, K., Logothetis, N., Besserve, M.
Neural mass modeling of the Ponto-Geniculo-Occipital wave and its neuromodulation
28th Annual Computational Neuroscience Meeting (CNS*2019), July 2019 (poster)
Li, G.
Reinforcement Learning for a Two-Robot Table Tennis Simulation
RWTH Aachen University, Germany, July 2019 (mastersthesis)
Konieczny, L.
Characteristics of longitudinal physiological measurements of late-stage ALS patients
Ludwig-Maximilians-Universität München, Germany, May 2019 (mastersthesis)
Scientific Report 2016 - 2018
2019 (mpi_year_book)
Xu, J.
Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing
Technical University of Munich, Germany, 2019 (mastersthesis)
2018
Goris, R., Henaff, O., Meding, K.
Representation of sensory uncertainty in macaque visual cortex
Computational and Systems Neuroscience (COSYNE) 2018, March 2018 (poster)
Bustamante, S.
A virtual reality environment for experiments in assistive robotics and neural interfaces
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)
Gebhard, T.
On the Applicability of Machine Learning to Aid the Search for Gravitational Waves at the LIGO Experiment
Karlsruhe Institute of Technology, Germany, 2018 (mastersthesis)
Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N. K., Besserve, M.
Generalized phase locking analysis of electrophysiology data
7th AREADNE Conference on Research in Encoding and Decoding of Neural Ensembles, 2018 (poster)
Suter, R.
A Causal Perspective on Deep Representation Learning
ETH Zurich, 2018 (mastersthesis)
Lechner, T.
Domain Adaptation Under Causal Assumptions
Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)
Schölkopf, B.
Maschinelles Lernen: Entwicklung ohne Grenzen?
In Mit Optimismus in die Zukunft schauen. Künstliche Intelligenz - Chancen und Rahmenbedingungen, pages: 26-34, (Editors: Bender, G. and Herbrich, R. and Siebenhaar, K.), B&S Siebenhaar Verlag, 2018 (incollection)
Zabel, S.
Improving Tissue Differentiation based on Optical Emission Spectroscopy for Guided Electrosurgical Tumor Resection with Machine Learning
Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)