Publications

Empirical Inference Article Impact of prospective motion correction, distortion correction methods and large vein bias on the spatial accuracy of cortical laminar fMRI at 9.4 Tesla Bause, J., Polimeni, J. R., Stelzer, J., In, M., Ehses, P., Kraemer-Fernandez, P., Aghaeifar, A., Lacosse, E., Pohmann, R., Scheffler, K. Neuroimage, 208, 2020 (Published) DOI BibTeX

Empirical Inference Article Incremental Learning of an Open-Ended Collaborative Skill Library Koert, D., Trick, S., Ewerton, M., Lutter, M., Peters, J. International Journal of Humanoid Robotics, 17(1), 2020 (Published) DOI BibTeX

Empirical Inference Article Independent attenuation correction of whole body [18F]FDG-PET using a deep learning approach with Generative Adversarial Networks Armanious, K., Hepp, T., Küstner, T., Dittmann, H., Nikolaou, K., La Fougère, C., Yang, B., Gatidis, S. EJNMMI Research, 10, 2020 (Published) DOI BibTeX

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

Empirical Inference Article Learning Attribute Grammars for Movement Primitive Sequencing Lioutikov, R., Maeda, G., Veiga, F., Kersting, K., Peters, J. The International Journal of Robotics Research (IJRR), 39(1):21-38, 2020 (Published) DOI BibTeX

Empirical Inference Conference Paper Learning Hierarchical Acquisition Functions for Bayesian Optimization Rottmann, N., Kunavar, T., Babic, J., Peters, J., Rueckert, E. International Conference on Intelligent Robots and Systems (IROS), :5490-5496, IEEE, 2020 (Published) DOI BibTeX

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

Empirical Inference Article Learning Sequential Force Interaction Skills Manschitz, S., Gienger, M., Kober, J., Peters, J. Robotics, 9(2):article no. 45, 2020 (Published) DOI BibTeX

Empirical Inference Article Longitudinal monitoring of apparent diffusion coefficient (ADC) in myeloma patients with lower M-gradient levels undergoing systemic treatment and whole-body MRI monitoring Perl, R. M., Gronbach, F., Fritz, J., Horger, M. S., Hepp, T. European Journal of Radiology, 132(article no. 109306), 2020 (Published) DOI BibTeX

Empirical Inference Conference Paper Model-Based Quality-Diversity Search for Efficient Robot Learning Keller, L., Tanneberg, D., Stark, S., Peters, J. International Conference on Intelligent Robots and Systems (IROS), :9675-9680, IEEE, 2020 (Published) DOI BibTeX

Empirical Inference Article Multi-Channel Interactive Reinforcement Learning for Sequential Tasks Koert, D., Kircher, M., Salikutluk, V., D’Eramo, C., Peters, J. Frontiers in Robotics and AI, 7(September), 2020 (Published) DOI BibTeX

Empirical Inference Article Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization Lauri, M., Pajarinen, J., Peters, J., Frintrop, S. IEEE Robotics and Automation Letters, 5(4):5323-5300, 2020 (Published) DOI BibTeX

Embodied Vision Empirical Inference Article Numerical Quadrature for Probabilistic Policy Search Vinogradska, J., Bischoff, B., Achterhold, J., Koller, T., Peters, J. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(1):164-175, 2020 (Published) DOI BibTeX

Empirical Inference Conference Paper Physically constrained causal noise models for high-contrast imaging of exoplanets Gebhard, T. D., Bonse, M. J., Quanz, S. P., Schölkopf, B. Machine Learning and the Physical Sciences - Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020 (Published) arXiv BibTeX

Empirical Inference Article Plucking Motions for Tea Harvesting Robots Using Probabilistic Movement Primitives Motokura, K., Takahashi, M., Ewerton, M., Peters, J. IEEE Robotics and Automation Letters, 5(2):3275-3282, 2020 (Published) DOI BibTeX

Empirical Inference Article Probabilistic Approach to Physical Object Disentangling Pajarinen, J., Arenz, O., Peters, J., Neumann, G. IEEE Robotics and Automation Letters, 5(4):5510-5517, 2020 (Published) DOI BibTeX

Empirical Inference Article SCIM: universal single-cell matching with unpaired feature sets Stark, S. G., Ficek, J., Locatello, F., Bonilla, X., Chevrier, S., Singer, F., Tumor Profiler Consortium, , Rätsch, G., Lehmann, K. Bioinformatics, 36:i919-i927, 2020, Supplement\textunderscore2 (Published) DOI BibTeX

Empirical Inference Conference Paper Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation Lu, C., Huang, B., Wang, K., Hernández-Lobato, J. M., Zhang, K., Schölkopf, B. Offline Reinforcement Learning - Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020 (Published) arXiv URL BibTeX

Empirical Inference Article Stratification of behavioral response to transcranial current stimulation by resting-state electrophysiology Mastakouri, A. A. bioRxiv, Cold Spring Harbor Laboratory, 2020 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Structured policy representation: Imposing stability in arbitrarily conditioned dynamic systems Urain, J., Tateo, D., Ren, T., Peters, J. 3rd Robot Learning Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020 (Published) URL BibTeX

Empirical Inference Article Training deep neural density estimators to identify mechanistic models of neural dynamics Gonçalves, P. J., Lueckmann, J., Deistler, M., Nonnenmacher, M., Öcal, K., Bassetto, G., Chintaluri, C., Podlaski, W. F., Haddad, S. A., Vogels, T. P., et al. eLife, 9:article no. e56261, (Editors: Huguenard, John R. and O’Leary, Timothy and Goldman, Mark S.), 2020 (Published) DOI BibTeX

Empirical Inference Article sbi: A toolkit for simulation-based inference Tejero-Cantero, A., Boelts, J., Deistler, M., Lueckmann, J., Durkan, C., Gonçalves, P. J., Greenberg, D. S., Macke, J. H. Journal of Open Source Software, 5(52):article no. 2505, 2020 (Published) DOI BibTeX

Empirical Inference Conference Paper Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks von Kügelgen, J., Rubenstein, P. K., Schölkopf, B., Weller, A. NeurIPS 2019 Workshop Do the right thing: machine learning and causal inference for improved decision making, December 2019 (Published) arXiv Poster URL BibTeX

Empirical Inference Conference Paper Fisher Efficient Inference of Intractable Models Liu, S., Kanamori, T., Jitkrittum, W., Chen, Y. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :8790-8800, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper A Model to Search for Synthesizable Molecules Bradshaw, J., Paige, B., Kusner, M. J., Segler, M., Hernández-Lobato, J. M. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :7935-7947, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Are Disentangled Representations Helpful for Abstract Visual Reasoning? van Steenkiste, S., Locatello, F., Schmidhuber, J., Bachem, O. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :14222-14235, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Convergence Guarantees for Adaptive Bayesian Quadrature Methods Kanagawa, M., Hennig, P. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :6234-6245, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Exploiting the modularity of deep networks to generate visual counterfactuals Besserve, M., Mehrjou, A., Sun, R., Schölkopf, B. NeurIPS 2019 - Workshop on Shared Visual Representations in Human & Machine Intelligence, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Flex-Convolution Groh*, F., Wieschollek*, P., Lensch, H. P. A. Computer Vision - ACCV 2018 - 14th Asian Conference on Computer Vision, 11361:105-122, Lecture Notes in Computer Science, (Editors: Jawahar, C. V. and Li, Hongdong and Mori, Greg and Schindler, Konrad), Springer International Publishing, December 2019, *equal contribution (Published) DOI BibTeX

Empirical Inference Conference Paper Invert to Learn to Invert Putzky, P., Welling, M. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :444-454, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Kernel Stein Tests for Multiple Model Comparison Lim, J. N., Yamada, M., Schölkopf, B., Jitkrittum, W. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :2240-2250, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Probabilistic Numerics Conference Paper Limitations of the empirical Fisher approximation for natural gradient descent Kunstner, F., Hennig, P., Balles, L. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :4158-4169, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Talk Multivariate coupling estimation between continuous signals and point processes Safavi, S., Logothetis, N., Besserve, M. Neural Information Processing Systems 2019 - Workshop on Learning with Temporal Point Processes, December 2019 (Published) Talk video URL BibTeX

Empirical Inference Conference Paper On the Fairness of Disentangled Representations Locatello, F., Abbati, G., Rainforth, T., Bauer, S., Schölkopf, B., Bachem, O. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :14584-14597, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Optics and Sensing Laboratory Autonomous Motion Conference Paper On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset Gondal, M. W., Wüthrich, M., Miladinovic, D., Locatello, F., Breidt, M., Volchkov, V., Akpo, J., Bachem, O., Schölkopf, B., Bauer, S. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :15714-15725, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Perceiving the arrow of time in autoregressive motion Meding, K., Janzing, D., Schölkopf, B., Wichmann, F. A. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :2303-2314, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Practical and Consistent Estimation of f-Divergences Rubenstein, P. K., Bousquet, O., Djolonga, J., Riquelme, C., Tolstikhin, I. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :4072-4082, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Ph.D. Thesis Real Time Probabilistic Models for Robot Trajectories Gomez-Gonzalez, S. Technical University Darmstadt, Germany, December 2019 (Published) BibTeX

Empirical Inference Ph.D. Thesis Robot Learning for Muscular Systems Büchler, D. Technical University Darmstadt, Germany, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Selecting causal brain features with a single conditional independence test per feature Mastakouri, A., Schölkopf, B., Janzing, D. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :12532-12543, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Stochastic Frank-Wolfe for Composite Convex Minimization Locatello, F., Yurtsever, A., Fercoq, O., Cevher, V. Advances in Neural Information Processing Systems 32 (NeurIPS 2019), :14246-14256, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Improving Local Trajectory Optimisation using Probabilistic Movement Primitives Shyam, R. A., Lightbody, P., Das, G., Liu, P., Gomez-Gonzalez, S., Neumann, G. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), :2666-2671, IEEE, International Conference on Intelligent Robots and Systems 2019 (IROS) , November 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Experience Reuse with Probabilistic Movement Primitives Stark, S., Peters, J., Rueckert, E. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), :1210-1217, IEEE, November 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Chance-Constrained Trajectory Optimization for Non-linear Systems with Unknown Stochastic Dynamics Celik, O., Abdulsamad, H., Peters, J. International Conference on Intelligent Robots and Systems (IROS), :6828-6833, IEEE, November 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems Lutter, M., Listmann, K., Peters, J. International Conference on Intelligent Robots and Systems (IROS), :7718-7725, IEEE, November 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Generalized Multiple Correlation Coefficient as a Similarity Measurement between Trajectories Urain, J., Peters, J. International Conference on Intelligent Robots and Systems (IROS), :1363-1369, IEEE, November 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction Trick, S., Koert, D., Peters, J., Rothkopf, C. A. International Conference on Intelligent Robots and Systems (IROS), :7009-7016, IEEE, November 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Receding Horizon Curiosity Schultheis, M., Belousov, B., Abdulsamad, H., Peters, J. Proceedings of the 3rd Annual Conference on Robot Learning (CoRL), 100:1278-1288, Proceedings of Machine Learning Research, (Editors: Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura), PMLR, November 2019 (Published) URL BibTeX

Empirical Inference Conference Paper Reinforcement Learning of Trajectory Distributions: Applications in Assisted Teleoperation and Motion Planning Ewerton, M., Guilherme, M., Koert, D., Kolev, Z., Takahashi, M., Peters, J. International Conference on Intelligent Robots and Systems (IROS), :4294-4300, IEEE, November 2019 (Published) DOI BibTeX

Empirical Inference Conference Paper Self-Paced Contextual Reinforcement Learning Klink, P., Abdulsamad, H., Belousov, B., Peters, J. Proceedings of the 3rd Annual Conference on Robot Learning (CoRL), 100:513-529, Proceedings of Machine Learning Research, (Editors: Leslie Pack Kaelbling and Danica Kragic and Komei Sugiura), PMLR, November 2019 (Published) URL BibTeX

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