Mastakouri, A., Schölkopf, B., Janzing, D.
Selecting causal brain features with a single conditional independence test per feature
Advances in Neural Information Processing Systems 32, 33rd Annual Conference on Neural Information Processing Systems, December 2019 (conference) Accepted
Ozdenizci, O., Meyer, T., Wichmann, F., Peters, J., Schölkopf, B., Cetin, M., Grosse-Wentrup, M.
Neural Signatures of Motor Skill in the Resting Brain
Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (SMC 2019), October 2019 (conference) Accepted
Mastakouri, A., Schölkopf, B., Grosse-Wentrup, M.
Beta Power May Mediate the Effect of Gamma-TACS on Motor Performance
Engineering in Medicine and Biology Conference (EMBC), July 2019 (conference) Accepted
Geiger, P., Besserve, M., Winkelmann, J., Proissl, C., Schölkopf, B.
Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory
Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), pages: 49, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019 (conference)
Kilbertus, N., Ball, P. J., Kusner, M. J., Weller, A., Silva, R.
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), pages: 213, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019 (conference)
Gresele*, L., Rubenstein*, P. K., Mehrjou, A., Locatello, F., Schölkopf, B.
The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA
Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), pages: 53, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019, *equal contribution (conference)
Peharz, R., Vergari, A., Stelzner, K., Molina, A., Shao, X., Trapp, M., Kersting, K., Ghahramani, Z.
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence (UAI), pages: 124, (Editors: Amir Globerson and Ricardo Silva), AUAI Press, July 2019 (conference)
Jitkrittum*, W., Sangkloy*, P., Gondal, M. W., Raj, A., Hays, J., Schölkopf, B.
Kernel Mean Matching for Content Addressability of GANs
Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 3140-3151, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019, *equal contribution (conference)
Locatello, F., Bauer, S., Lucic, M., Raetsch, G., Gelly, S., Schölkopf, B., Bachem, O.
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 4114-4124, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)
Zhang, Y., Tang, S., Muandet, K., Jarvers, C., Neumann, H.
Local Temporal Bilinear Pooling for Fine-grained Action Parsing
In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2019, June 2019 (inproceedings)
Jitkrittum*, W., Sangkloy*, P., Gondal, M. W., Raj, A., Hays, J., Schölkopf, B.
Generate Semantically Similar Images with Kernel Mean Matching
6th Workshop Women in Computer Vision (WiCV) (oral presentation), June 2019, *equal contribution (conference) Accepted
Akrour, R., Pajarinen, J., Peters, J., Neumann, G.
Projections for Approximate Policy Iteration Algorithms
Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 181-190, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)
Becker-Ehmck, P., Peters, J., van der Smagt, P.
Switching Linear Dynamics for Variational Bayes Filtering
Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 553-562, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)
Suter, R., Miladinovic, D., Schölkopf, B., Bauer, S.
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 6056-6065, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)
Simon-Gabriel, C., Ollivier, Y., Bottou, L., Schölkopf, B., Lopez-Paz, D.
First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 5809-5817, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (conference)
Ialongo, A. D., Van Der Wilk, M., Hensman, J., Rasmussen, C. E.
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
In Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 2931-2940, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, June 2019 (inproceedings)
Gordon, J., Bronskill, J., Bauer, M., Nowozin, S., Turner, R.
Meta learning variational inference for prediction
7th International Conference on Learning Representations (ICLR), May 2019 (conference)
Lutter, M., Ritter, C., Peters, J.
Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
7th International Conference on Learning Representations (ICLR), May 2019 (conference)
Schneider, F., Balles, L., Hennig, P.
DeepOBS: A Deep Learning Optimizer Benchmark Suite
7th International Conference on Learning Representations (ICLR), May 2019 (conference)
Miladinović*, D., Gondal*, M. W., Schölkopf, B., Buhmann, J. M., Bauer, S.
Disentangled State Space Models: Unsupervised Learning of Dynamics across Heterogeneous Environments
Deep Generative Models for Highly Structured Data Workshop at ICLR, May 2019, *equal contribution (conference)
Fortuin, V., Hüser, M., Locatello, F., Strathmann, H., Rätsch, G.
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
7th International Conference on Learning Representations (ICLR), May 2019 (conference)
Bauer, M., Mnih, A.
Resampled Priors for Variational Autoencoders
22nd International Conference on Artificial Intelligence and Statistics, April 2019 (conference) Accepted
von Kügelgen, J., Mey, A., Loog, M.
Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1361-1369, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)
Mroueh, Y., Sercu, T., Raj, A.
Sobolev Descent
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 2976-2985, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)
Arvanitidis, G., Hauberg, S., Hennig, P., Schober, M.
Fast and Robust Shortest Paths on Manifolds Learned from Data
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1506-1515, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)
de Roos, F., Hennig, P.
Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1448-1457, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)
Wenk, P., Gotovos, A., Bauer, S., Gorbach, N., Krause, A., Buhmann, J. M.
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1351-1360, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)
Mehrjou, A., Jitkrittum, W., Schölkopf, B., Muandet, K.
Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces
2019 (conference) Submitted
Abbati*, G., Wenk*, P., Osborne, M. A., Krause, A., Schölkopf, B., Bauer, S.
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs
Proceedings of the 36th International Conference on Machine Learning (ICML), 97, pages: 1-10, Proceedings of Machine Learning Research, (Editors: Chaudhuri, Kamalika and Salakhutdinov, Ruslan), PMLR, 2019, *equal contribution (conference)
Lim, J. N., Yamada, M., Schölkopf, B., Jitkrittum, W.
Kernel Stein Tests for Multiple Model Comparison
Advances in Neural Information Processing Systems 32, 33rd Annual Conference on Neural Information Processing Systems, 2019 (conference) To be published
Hohmann, M. R., Hackl, M., Wirth, B., Zaman, T., Enficiaud, R., Grosse-Wentrup, M., Schölkopf, B.
MYND: A Platform for Large-scale Neuroscientific Studies
Proceedings of the 2019 Conference on Human Factors in Computing Systems (CHI), 2019 (conference) Accepted
Kanagawa, H., Jitkrittum, W., Mackey, L., Fukumizu, K., Gretton, A.
A Kernel Stein Test for Comparing Latent Variable Models
2019 (conference) Submitted
Ghosh*, P., Sajjadi*, M. S. M., Vergari, A., Black, M. J., Schölkopf, B.
From Variational to Deterministic Autoencoders
2019, *equal contribution (conference) Submitted
Liu, S., Kanamori, T., Jitkrittum, W., Chen, Y.
Fisher Efficient Inference of Intractable Models
Advances in Neural Information Processing Systems 32, 33rd Annual Conference on Neural Information Processing Systems, 2019 (conference) To be published
Calandra, R., Ivaldi, S., Deisenroth, M., Peters, J.
Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin
In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 690-695, Humanoids, November 2015 (inproceedings)
Hoelscher, J., Peters, J., Hermans, T.
Evaluation of Interactive Object Recognition with Tactile Sensing
In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 310-317, Humanoids, November 2015 (inproceedings)
Harmeling, S., Hirsch, M., Sra, S., Schölkopf, B., Schuler, C.
Method and device for recovering a digital image from a sequence of observed digital images
European Patent, No. 11767924.1, November 2015 (patent)
Koc, O., Maeda, G., Neumann, G., Peters, J.
Optimizing Robot Striking Movement Primitives with Iterative Learning Control
In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 80-87, Humanoids, November 2015 (inproceedings)
Leischnig, S., Luettgen, S., Kroemer, O., Peters, J.
A Comparison of Contact Distribution Representations for Learning to Predict Object Interactions
In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 616-622, Humanoids, November 2015 (inproceedings)
Fritsche, L., Unverzagt, F., Peters, J., Calandra, R.
First-Person Tele-Operation of a Humanoid Robot
In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 997-1002, Humanoids, November 2015 (inproceedings)
Lioutikov, R., Neumann, G., Maeda, G., Peters, J.
Probabilistic Segmentation Applied to an Assembly Task
In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 533-540, Humanoids, November 2015 (inproceedings)
Marco, A., Hennig, P., Bohg, J., Schaal, S., Trimpe, S.
Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results
Machine Learning in Planning and Control of Robot Motion Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS), pages: , , Machine Learning in Planning and Control of Robot Motion Workshop, October 2015 (conference)
Tolstikhin, I., Zhivotovskiy, N., Blanchard, G.
Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning
In Proceedings of the 26th International Conference on Algorithmic Learning Theory, 9355, pages: 209-223, Lecture Notes in Computer Science, (Editors: K. Chaudhuri, C. Gentile and S. Zilles), Springer, ALT, October 2015 (inproceedings)
Besserve, M.
Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism
53rd Annual Allerton Conference on Communication, Control, and Computing, September 2015 (talk)
Veiga, F., van Hoof, H., Peters, J., Hermans, T.
Stabilizing Novel Objects by Learning to Predict Tactile Slip
In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 5065-5072, IROS, September 2015 (inproceedings)
Paraschos, A., Rueckert, E., Peters, J., Neumann, G.
Model-Free Probabilistic Movement Primitives for Physical Interaction
In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 2860-2866, IROS, September 2015 (inproceedings)
Wahrburg, A., Zeiss, S., Matthias, B., Peters, J., Ding, H.
Combined Pose-Wrench and State Machine Representation for Modeling Robotic Assembly Skills
In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 852-857, IROS, September 2015 (inproceedings)
Manschitz, S., Kober, J., Gienger, M., Peters, J.
Probabilistic Progress Prediction and Sequencing of Concurrent Movement Primitives
In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 449-455, IROS, September 2015 (inproceedings)
Parisi, S., Abdulsamad, H., Paraschos, A., Daniel, C., Peters, J.
Reinforcement Learning vs Human Programming in Tetherball Robot Games
In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 6428-6434, IROS, September 2015 (inproceedings)
Ewerton, M., Maeda, G., Peters, J., Neumann, G.
Learning Motor Skills from Partially Observed Movements Executed at Different Speeds
In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 456-463, IROS, September 2015 (inproceedings)