von Kügelgen, J. Identifiable Causal Representation Learning University of Cambridge, UK, Cambridge, February 2024, (Cambridge-Tübingen-Fellowship) (phdthesis)

[BibTex]

Karimi, A. Advances in Algorithmic Recourse: Ensuring Causal Consistency, Fairness, & Robustness ETH Zurich, Switzerland, July 2023 (phdthesis)

[BibTex]

Kübler, J. M. Learning and Testing Powerful Hypotheses University of Tübingen, Germany, July 2023 (phdthesis)

[BibTex]

Gresele, L. Learning Identifiable Representations: Independent Influences and Multiple Views University of Tübingen, Germany, June 2023 (phdthesis)

[BibTex]

Paulus, M. Learning with and for discrete optimization (ETH Zurich, Switzerland), May 2023, CLS PhD Program (phdthesis)

[BibTex]

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

PDF [BibTex]

Neitz, A. Towards learning mechanistic models at the right level of abstraction University of Tübingen, Germany, November 2022 (phdthesis)

[BibTex]

Lu, C. Learning Causal Representations for Generalization and Adaptation in Supervised, Imitation, and Reinforcement Learning University of Cambridge, UK, Cambridge, October 2022, (Cambridge-Tübingen-Fellowship) (phdthesis)

[BibTex]

Tabibian, B. Methods for Minimizing the Spread of Misinformation on the Web University of Tübingen, Germany, September 2022 (phdthesis)

[BibTex]

Huang, B. Learning and Using Causal Knowledge: A Further Step Towards a Higher-Level Intelligence Carnegie Mellon University, Pittsburgh, USA, July 2022 (phdthesis)

[BibTex]

Schölkopf, B., Uhler, C., Zhang, K. Proceedings of the First Conference on Causal Learning and Reasoning (CLeaR 2022) 177, Proceedings of Machine Learning Research, PMLR, April 2022 (proceedings)

link (url) [BibTex]

Ialongo, A. Variational Inference in Dynamical Systems University of Cambridge, UK, Cambridge, February 2022, (Cambridge-Tübingen-Fellowship) (phdthesis)

[BibTex]

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]

Mehrjou, A. Dynamics of Learning and Learning of Dynamics ETH Zürich, Zürich, October 2021 (phdthesis)

DOI [BibTex]

Hohmann, M. A Large Scale Brain-Computer Interface for Patients with Neurological Diseases University of Tübingen, Germany, September 2021 (phdthesis)

[BibTex]

Parascandolo, G. Deep Learning Beyond The Training Distribution ETH Zürich, Switzerland, Zürich, September 2021, (CLS Fellowship Program) (phdthesis)

DOI [BibTex]

Field, A., Prabhumoye, S., Sap, M., Jin, Z., Zhao, J., Brockett, C. Proceedings of the 1st Workshop on NLP for Positive Impact Association for Computational Linguistics, August 2021 (proceedings)

link (url) [BibTex]

Raj, A. Optimization Algorithms for Machine Learning University of Tübingen, Germany, June 2021 (phdthesis)

[BibTex]

Meding, K. Causal Inference in Vision Eberhard Karls Universität Tübingen, Tübingen, June 2021 (phdthesis)

[BibTex]

Bradshaw, J. Machine Learning Methods for Modeling Synthesizable Molecules University of Cambridge, UK, Cambridge, April 2021, (Cambridge-Tübingen-Fellowship) (phdthesis)

DOI [BibTex]

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]

Panda, S., Shen, C., Perry, R., Zorn, J., Lutz, A., Priebe, C. E., Vogelstein, J. T. Nonpar MANOVA via Independence Testing 2021 (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]

Perry, R., Tomita, T. M., Mehta, R., Arroyo, J., Patsolic, J., Falk, B., Vogelstein, J. T. Manifold forests: closing the gap on neural networks 2021 (misc)

arXiv [BibTex]

Perry, R., Mehta, R., Guo, R., Yezerets, E., Arroyo, J., Powell, M., Helm, H., Shen, C., Vogelstein, J. T. Random Forests for Adaptive Nearest Neighbor Estimation of Information-Theoretic Quantities 2021 (misc)

arXiv [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]

Mastakouri, A. Causal Feature Selection in Neuroscience University of Tübingen, Germany, December 2020 (phdthesis)

link (url) [BibTex]

Locatello, F. Enforcing and Discovering Structure in Machine Learning ETH Zurich, Switzerland, November 2020, (CLS Fellowship Program) (phdthesis)

[BibTex]

Bécigneul, G. On the Geometry of Data Representations ETH Zurich, Switzerland, September 2020, (CLS Fellowship Program) (phdthesis)

[BibTex]

Kilbertus, N. Beyond traditional assumptions in fair machine learning University of Cambridge, UK, September 2020, (Cambridge-Tübingen-Fellowship) (phdthesis)

[BibTex]

Rubenstein, P. Advances in Latent Variable and Causal Models University of Cambridge, UK, July 2020, (Cambridge-Tuebingen-Fellowship) (phdthesis)

[BibTex]

Wieschollek, P. Learning from Multi-Frame Data University of Tübingen, Germany, July 2020 (phdthesis)

[BibTex]

Balog, M. Converting to Optimization in Machine Learning: Perturb-and-MAP, Differential Privacy, and Program Synthesis University of Cambridge, UK, July 2020, (Cambridge-Tübingen-Fellowship) (phdthesis)

[BibTex]

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]

Jin, D., Jin, Z., Mihalcea, R. Deep Learning for Text Attribute Transfer: A Survey 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]

Jin, Z., Yang, Y., Qiu, X., Zhang, Z. Relation of the Relations: A New Paradigm of the Relation Extraction Problem 2020 (misc)

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]

Büchler, D. Robot Learning for Muscular Systems Technical University Darmstadt, Germany, December 2019 (phdthesis)

link (url) [BibTex]

Gomez-Gonzalez, S. Real Time Probabilistic Models for Robot Trajectories Technical University Darmstadt, Germany, December 2019 (phdthesis)

[BibTex]

Rojas-Carulla, M. Learning Transferable Representations University of Cambridge, UK, February 2019 (phdthesis)

[BibTex]

Gu, S. Sample-efficient deep reinforcement learning for continuous control University of Cambridge, UK, 2019 (phdthesis)

[BibTex]

Weichwald, S. Pragmatism and Variable Transformations in Causal Modelling ETH Zurich, 2019 (phdthesis)

[BibTex]

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

arXiv [BibTex]