Andrussow, I., Sun, H., Martius, G., Kuchenbecker, K. J. Demonstration: Minsight - A Soft Vision-Based Tactile Sensor for Robotic Fingertips Hands-on demonstration presented at the Conference on Robot Learning (CoRL), Munich, Germany, November 2024 (misc) Accepted

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Ortu, F. Interpreting How Large Language Models Handle Facts and Counterfactuals through Mechanistic Interpretability University of Trieste, Italy, March 2024 (mastersthesis)

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Bonse, M. J., Gebhard, T. D., Dannert, F. A., Absil, O., Cantalloube, F., Christiaens, V., Cugno, G., Garvin, E. O., Hayoz, J., Kasper, M., Matthews, E., Schölkopf, B., Quanz, S. P. Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning reveals the Giant Exoplanet AF Lep b in High-Contrast Imaging Data from 2011 2024 (misc) Submitted

arXiv [BibTex]

Buchholz, S., Kübler, J. M., Schölkopf, B. Multi-Armed Bandits and Quantum Channel Oracles 2024 (misc)

arXiv [BibTex]

Rajendran, G., Buchholz, S., Aragam, B., Schölkopf, B., Ravikumar, P. Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models 2024 (misc)

arXiv [BibTex]

Sakenyte, U. Denoising Representation Learning for Causal Discovery Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)

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Kofler, A. Efficient Sampling from Differentiable Matrix Elements Technical University of Munich, Germany, September 2023 (mastersthesis)

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Spieler, A. M. Intrinsic complexity and mechanisms of expressivity of cortical neurons University of Tübingen, Germany, March 2023 (mastersthesis)

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Kladny, K. CausalEffect Estimation by Combining Observational and Interventional Data ETH Zurich, Switzerland, February 2023 (mastersthesis)

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Qui, Z. Towards Generative Machine Teaching Technical University of Munich, Germany, February 2023 (mastersthesis)

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Schneider, F. ArchiSound: Audio Generation with Diffusion ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)

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Dittrich, A. Generation and Quantification of Spin in Robot Table Tennis University of Stuttgart, Germany, January 2023 (mastersthesis)

[BibTex]

Bottou, L., Schölkopf, B. Borges und die Künstliche Intelligenz 2023, published in Frankfurter Allgemeine Zeitung, 18 December 2023, Nr. 294 (misc)

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Liang, W. Investigating Independent Mechanisms in Neural Networks Université Paris-Saclay, France, October 2022 (mastersthesis)

[BibTex]

Keidar, D. Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones ETH Zurich, Switzerland, October 2022 (mastersthesis)

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Feil, M. Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning Technnical University Munich, Germany, September 2022 (mastersthesis)

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Sliwa, J. Independent Mechanism Analysis for High Dimensions University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)

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Dominguez-Olmedo, R. On the Adversarial Robustness of Causal Algorithmic Recourse University of Tübingen, Germany, August 2022 (mastersthesis)

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Ghosh, S. Independent Mechanism Analysis in High-Dimensional Observation Spaces ETH Zurich, Switzerland, June 2022 (mastersthesis)

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Wang, H., Jin, Z., Cao, J., Fung, G. P. C., Wong, K. Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning 2022 (misc)

arXiv [BibTex]

Scherrer, N. Learning Neural Causal Models with Active Interventions ETH Zurich, Switzerland, November 2021 (mastersthesis)

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Bing, S. HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Lanzillotta, G. Study of the Interventional Consistency of Autoencoders ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Mambelli, D. Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Prabhoo, S., Bauer, S., Schwab, P. NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments 2021 (misc)

arXiv [BibTex]

Abdulsamad, H., Dorau, T., Belousov, B., Zhu, J., Peters, J. Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative-Entropy Trust Regions 2021 (misc)

arXiv Project Page [BibTex]

Arvanitidis, G., González Duque, M., Pouplin, A., Kalatzis, D., Hauberg, S. Pulling back information geometry 2021 (misc)

arXiv [BibTex]

Wüthrich*, M., Widmaier*, F., Bauer*, S., Funk, N., Urain, J., Peters, J., Watson, J., Chen, C., Srinivasan, K., Zhang, J., Zhang, J., Walter, M. R., Madan, R., Schaff, C., Maeda, T., Yoneda, T., Yarats, D., Allshire, A., Gordon, E. K., Bhattacharjee, T., Srinivasa, S. S., Garg, A., Buchholz, A., Stark, S., Steinbrenner, T., Akpo, J., Joshi, S., Agrawal, V., Schölkopf, B. A Robot Cluster for Reproducible Research in Dexterous Manipulation 2021, *equal contribution (misc)

arXiv [BibTex]

Shao, K., Villegas, J. F. R., Logothetis, N. K., Besserve, M. A model of Ponto-Geniculo-Occipital waves supports bidirectional control of cortical plasticity across sleep-stages 2021 (misc) In preparation

bioRxiv DOI [BibTex]

Georgiev, B., Franken, L., Mukherjee, M., Arvanitidis, G. On the Impact of Stable Ranks in Deep Nets 2021 (misc)

arXiv [BibTex]

Scientific Report 2016 - 2021 2021 (mpi_year_book)

Scientific Report 2016 - 2021 [BibTex]

Allshire, A., Mittal, M., Lodaya, V., Makoviychuk, V., Makoviichuk, D., Widmaier, F., Wüthrich, M., Bauer, S., Handa, A., Garg, A. Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger 2021 (misc)

arXiv [BibTex]

Ahmed, O. A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning ETH Zurich, Switzerland, October 2020 (mastersthesis)

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DuMont Schütte, A. A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging ETH Zurich, Switzerland, October 2020 (mastersthesis)

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Cacioppo, A. Deep learning for the parameter estimation of tight-binding Hamiltonians University of Roma, La Sapienza, Italy, May 2020 (mastersthesis)

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Zecevic, M. Learning Algorithms, Invariances, and the Real World Technical University of Darmstadt, Germany, April 2020 (mastersthesis)

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Chicharro, D., Besserve, M., Panzeri, S. Causal learning with sufficient statistics: an information bottleneck approach 2020 (misc) Submitted

arXiv [BibTex]

Träuble, F., Creager, E., Kilbertus, N., Goyal, A., Locatello, F., Schölkopf, B., Bauer, S. Is Independence all you need? On the Generalization of Representations Learned from Correlated Data 2020 (misc)

link (url) [BibTex]

Tosatto, S., Stadtmueller, J., Peters, J. Dimensionality Reduction of Movement Primitives in Parameter Space 2020 (misc)

arXiv [BibTex]

Besserve, M., Buchholz, S., Schölkopf, B. Assaying Large-scale Testing Models to Interpret Covid-19 Case Numbers. A Cross-country Study 2020 (misc) Submitted

arXiv [BibTex]

Ke, R., Bilaniuk, O., Goyal, A., Bauer, S., Larochelle, H., Schölkopf, B., Mozer, M. C., Pal, C., Bengio, Y. Learning Neural Causal Models from Unknown Interventions 2020 (misc)

arXiv Project Page [BibTex]

Stimper, V. Inferring the Band Structure from Band Mapping Data through Machine Learning Technical University of Munich, September 2019 (mastersthesis)

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Dietz, B. Learning to Diagnose Diabetes from Magnetic Resonance Tomography ETH Zurich, Switzerland, August 2019 (mastersthesis)

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Li, G. Reinforcement Learning for a Two-Robot Table Tennis Simulation RWTH Aachen University, Germany, July 2019 (mastersthesis)

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Konieczny, L. Characteristics of longitudinal physiological measurements of late-stage ALS patients Ludwig-Maximilians-Universität München, Germany, May 2019 (mastersthesis)

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Park, M., Jitkrittum, W. ABCDP: Approximate Bayesian Computation Meets Differential Privacy 2019 (misc) Submitted

arXiv [BibTex]

Scientific Report 2016 - 2018 2019 (mpi_year_book)

Scientific Report 2016 - 2018 [BibTex]

Pfister, N., Bauer, S., Peters, J. Identifying Causal Structure in Large-Scale Kinetic Systems 2019 (misc)

link (url) [BibTex]

Xu, J. Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing Technical University of Munich, Germany, 2019 (mastersthesis)

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Tanneberg, D., Rueckert, E., Peters, J. Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer Architecture 2019 (misc)

arXiv [BibTex]