Publications

Empirical Inference Article Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks Tanneberg, D., Peters, J., Rueckert, E. Neural Networks, 109:67-80, 2018 (Published) DOI URL BibTeX

Empirical Inference Article Invariant Models for Causal Transfer Learning Rojas-Carulla, M., Schölkopf, B., Turner, R., Peters, J. Journal of Machine Learning Research, 19(36):1-34, 2018 (Published) URL BibTeX

Empirical Inference Article Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling Šošić, A., Rueckert, E., Peters, J., Zoubir, A., Koeppl, H. Journal of Machine Learning Research, 19(69):1-45, 2018 (Published) URL BibTeX

Empirical Inference Article Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions Simon-Gabriel, C. J., Schölkopf, B. Journal of Machine Learning Research, 19(44):1-29, 2018 (Published) URL arXiv_long version BibTeX

Empirical Inference Article Kernel-based tests for joint independence Pfister, N., Bühlmann, P., Schölkopf, B., Peters, J. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 80(1):5-31, 2018 (Published) DOI BibTeX

Empirical Inference Probabilistic Numerics Statistical Learning Theory Miscellaneous Large sample analysis of the median heuristic Garreau, D., Jitkrittum, W., Kanagawa, M. 2018, In preparation (In preparation) arXiv BibTeX

Empirical Inference Article Learning Causality and Causality-Related Learning: Some Recent Progress Zhang, K., Schölkopf, B., Spirtes, P., Glymour, C. National Science Review, 5(1):26-29, 2018 (Published) DOI BibTeX

Empirical Inference Article Linking imaging to omics utilizing image-guided tissue extraction Disselhorst, J. A., Krueger, M. A., Ud-Dean, S. M. M., Bezrukov, I., Jarboui, M. A., Trautwein, C., Traube, A., Spindler, C., Cotton, J. M., Leibfritz, D., et al. Proceedings of the National Academy of Sciences, 115(13):E2980-E2987, 2018 (Published) DOI BibTeX

Empirical Inference Article MOABB: Trustworthy algorithm benchmarking for BCIs Jayaram, V., Barachant, A. Journal of Neural Engineering, 15(6):article no. 066011, 2018 (Published) DOI URL BibTeX

Empirical Inference Book Chapter Maschinelles Lernen: Entwicklung ohne Grenzen? Schölkopf, B. In Mit Optimismus in die Zukunft schauen. Künstliche Intelligenz - Chancen und Rahmenbedingungen, :26-34, (Editors: Bender, G. and Herbrich, R. and Siebenhaar, K.), B&S Siebenhaar Verlag, 2018 (Published) BibTeX

Empirical Inference Book Chapter Methods in Psychophysics Wichmann, F. A., Jäkel, F. In Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience, 5 (Methodology), 7, 4th, John Wiley & Sons, Inc., 2018 (Published) BibTeX

Empirical Inference Master Thesis On the Applicability of Machine Learning to Aid the Search for Gravitational Waves at the LIGO Experiment Gebhard, T. Karlsruhe Institute of Technology, Germany, 2018 (Published) BibTeX

Empirical Inference Conference Paper Online Learning of an Open-Ended Skill Library for Collaborative Tasks Koert, D., Trick, S., Ewerton, M., Lutter, M., Peters, J. IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), :1-9, 2018 (Published) DOI BibTeX

Empirical Inference Article Online optimal trajectory generation for robot table tennis Koc, O., Maeda, G., Peters, J. Robotics and Autonomous Systems, 105:121-137, 2018 (Published) PDF DOI URL BibTeX

Empirical Inference Ph.D. Thesis Optimal Trajectory Generation and Learning Control for Robot Table Tennis Koc, O. Technical University Darmstadt, Germany, 2018 (Published) BibTeX

Empirical Inference Poster Photorealistic Video Super Resolution Pérez-Pellitero, E., Sajjadi, M. S. M., Hirsch, M., Schölkopf, B. Workshop and Challenge on Perceptual Image Restoration and Manipulation (PIRM) at the 15th European Conference on Computer Vision (ECCV), 2018 (Published) BibTeX

Empirical Inference Article Phylogenetic convolutional neural networks in metagenomics Fioravanti*, D., Giarratano*, Y., Maggio*, V., Agostinelli, C., Chierici, M., Jurman, G., Furlanello, C. BMC Bioinformatics, 19(2):49 pages, 2018, *equal contribution (Published) DOI BibTeX

Empirical Inference Article Prediction of Glucose Tolerance without an Oral Glucose Tolerance Test Babbar, R., Heni, M., Peter, A., Hrabě de Angelis, M., Häring, H., Fritsche, A., Preissl, H., Schölkopf, B., Wagner, R. Frontiers in Endocrinology, 9:article no. 82, 2018 (Published) DOI BibTeX

Empirical Inference Probabilistic Numerics Ph.D. Thesis Probabilistic Approaches to Stochastic Optimization Mahsereci, M. Eberhard Karls Universität Tübingen, Germany, 2018 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper Probabilistic Deep Learning using Random Sum-Product Networks Peharz, R., Vergari, A., Stelzner, K., Molina, A., Trapp, M., Kersting, K., Ghahramani, Z. 2018, Submitted (Submitted) arXiv BibTeX

Empirical Inference Probabilistic Numerics Ph.D. Thesis Probabilistic Ordinary Differential Equation Solvers — Theory and Applications Schober, M. Eberhard Karls Universität Tübingen, Germany, 2018 (Published) BibTeX

Empirical Inference Article Quantum machine learning: a classical perspective Ciliberto, C., Herbster, M., Ialongo, A. D., Pontil, M., Rocchetto, A., Severini, S., Wossnig, L. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 474(2209):article no. 20170551, 2018 (Published) DOI URL BibTeX

Empirical Inference Master Thesis Reinforcement Learning for High-Speed Robotics with Muscular Actuation Guist, S. Ruprecht-Karls-Universität Heidelberg , 2018 (Published) BibTeX

Empirical Inference Poster Retinal image quality of the human eye across the visual field Meding, K., Hirsch, M., Wichmann, F. A. 14th Biannual Conference of the German Society for Cognitive Science (KOGWIS 2018), 2018 (Published) BibTeX

Empirical Inference Book Chapter Transfer Learning for BCIs Jayaram, V., Fiebig, K., Peters, J., Grosse-Wentrup, M. In Brain–Computer Interfaces Handbook, :425-442, 22, (Editors: Chang S. Nam, Anton Nijholt and Fabien Lotte), CRC Press, 2018 (Published) BibTeX

Empirical Inference Conference Paper Utilizing Human Feedback in POMDP Execution and Specification Hoelscher, J., Koert, D., Peters, J., Pajarinen, J. IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), :104-111, IEEE, 2018 (Published) DOI BibTeX

Empirical Inference Probabilistic Learning Group Article Visualizing and understanding Sum-Product Networks Vergari, A., Di Mauro, N., Esposito, F. Machine Learning, 2018 (Published) DOI BibTeX

Empirical Inference Conference Paper k–SVRG: Variance Reduction for Large Scale Optimization Raj, A., Stich, S. In 2018, Submitted (Submitted) BibTeX

Empirical Inference Conference Paper AdaGAN: Boosting Generative Models Tolstikhin, I., Gelly, S., Bousquet, O., Simon-Gabriel, C. J., Schölkopf, B. Advances in Neural Information Processing Systems 30 (NIPS 2017), :5424-5433, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., 31st Annual Conference on Neural Information Processing Systems, December 2017 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Avoiding Discrimination through Causal Reasoning Kilbertus, N., Rojas-Carulla, M., Parascandolo, G., Hardt, M., Janzing, D., Schölkopf, B. Advances in Neural Information Processing Systems 30 (NIPS 2017), :656-666, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., 31st Annual Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Boosting Variational Inference: an Optimization Perspective Locatello, F., Khanna, R., Ghosh, J., Rätsch, G. Workshop: Advances in Approximate Bayesian Inference at the 31st Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper ConvWave: Searching for Gravitational Waves with Fully Convolutional Neural Nets Gebhard, T., Kilbertus, N., Parascandolo, G., Harry, I., Schölkopf, B. Workshop on Deep Learning for Physical Sciences (DLPS) at the 31st Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Probabilistic Learning Group Conference Paper From Parity to Preference-based Notions of Fairness in Classification Zafar, M. B., Valera, I., Gomez Rodriguez, M., Gummadi, K., Weller, A. Advances in Neural Information Processing Systems 30 (NIPS 2017), :229-239, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., 31st Annual Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees Locatello, F., Tschannen, M., Rätsch, G., Jaggi, M. Advances in Neural Information Processing Systems 30 (NIPS 2017), :773-784, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., 31st Annual Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning Gu, S., Lillicrap, T., Turner, R. E., Ghahramani, Z., Schölkopf, B., Levine, S. Advances in Neural Information Processing Systems 30 (NIPS 2017), :3849-3858, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., 31st Annual Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Learning Independent Causal Mechanisms Parascandolo, G., Rojas-Carulla, M., Kilbertus, N., Schölkopf, B. Workshop: Learning Disentangled Representations: from Perception to Control at the 31st Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Safe Adaptive Importance Sampling Stich, S. U., Raj, A., Jaggi, M. Advances in Neural Information Processing Systems 30 (NIPS 2017), :4384-4394, (Editors: Guyon I. and Luxburg U.v. and Bengio S. and Wallach H. and Fergus R. and Vishwanathan S. and Garnett R.), Curran Associates, Inc., 31st Annual Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Closed-form Inference and Prediction in Gaussian Process State-Space Models Ialongo, A. D., Van Der Wilk, M., Rasmussen, C. E. Time Series Workshop at the 31st Conference on Neural Information Processing Systems, December 2017 (Published) PDF BibTeX

Empirical Inference Conference Paper Discriminative k-shot learning using probabilistic models Bauer*, M., Rojas-Carulla*, M., Świątkowski, J. B., Schölkopf, B., Turner, R. E. Second Workshop on Bayesian Deep Learning at the 31st Conference on Neural Information Processing Systems , December 2017, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Learning Robust Video Synchronization without Annotations Wieschollek, P., Freeman, I., Lensch, H. P. A. 16th IEEE International Conference on Machine Learning and Applications (ICMLA), :92 - 100, (Editors: X. Chen, B. Luo, F. Luo, V. Palade, and M. A. Wani), IEEE, December 2017 (Published) DOI BibTeX

Empirical Inference Conference Paper Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation Kim, J., Tabibian, B., Oh, A., Schölkopf, B., Gomez Rodriguez, M. Workshop on Prioritising Online Content at the 31st Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Optimizing human learning Tabibian, B., Upadhyay, U., De, A., Zarezade, A., Schölkopf, B., Gomez Rodriguez, M. Workshop on Teaching Machines, Robots, and Humans at the 31st Conference on Neural Information Processing Systems, December 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows Huang, B., Zhang, K., Zhang, J., Sanchez-Romero, R., Glymour, C., Schölkopf, B. IEEE 17th International Conference on Data Mining (ICDM), :913-918, (Editors: Vijay Raghavan,Srinivas Aluru, George Karypis, Lucio Miele and Xindong Wu), November 2017 (Published) DOI BibTeX

Empirical Inference Conference Paper A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries Stark, S., Peters, J., Rueckert, E. IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), :624-630, IEEE, November 2017 (Published) DOI BibTeX

Empirical Inference Conference Paper Active Incremental Learning of Robot Movement Primitives Maeda, G., Ewerton, M., Osa, T., Busch, B., Peters, J. Proceedings of the 1st Annual Conference on Robot Learning (CoRL), 78:37-46, Proceedings of Machine Learning Research, (Editors: Sergey Levine, Vincent Vanhoucke and Ken Goldberg), PMLR, November 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Efficient Online Adaptation with Stochastic Recurrent Neural Networks Tanneberg, D., Peters, J., Rueckert, E. IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), :198-204, IEEE, November 2017 (Published) DOI BibTeX

Empirical Inference Conference Paper End-to-End Learning for Image Burst Deblurring Wieschollek, P., Schölkopf, B., Lensch, H. P. A., Hirsch, M. Computer Vision - ACCV 2016 - 13th Asian Conference on Computer Vision, 10114:35-51, Image Processing, Computer Vision, Pattern Recognition, and Graphics, (Editors: Lai, S.-H., Lepetit, V., Nishino, K., and Sato, Y. ), Springer, November 2017 (Published) BibTeX

Empirical Inference Conference Paper Learning inverse dynamics models in O(n) time with LSTM networks Rueckert, E., Nakatenus, M., Tosatto, S., Peters, J. IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids), :811-816, IEEE, November 2017 (Published) DOI BibTeX

Empirical Inference Conference Paper Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals Tanneberg, D., Peters, J., Rueckert, E. Proceedings of the 1st Annual Conference on Robot Learning (CoRL), :167-174, Proceedings of Machine Learning Research, (Editors: Sergey Levine, Vincent Vanhoucke and Ken Goldberg), PMLR, November 2017 (Published) URL BibTeX

Empirical Inference Conference Paper Simulation of the underactuated Sake Robotics Gripper in V-REP Thiem, S., Stark, S., Tanneberg, D., Peters, J., Rueckert, E. Workshop at the International Conference on Humanoid Robots (HUMANOIDS), November 2017 (Published) URL BibTeX

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