ei
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
ei
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
re
Jain, Y. R., Gupta, S., Rakesh, V., Dayan, P., Callaway, F., Lieder, F.
How do people learn how to plan?
Conference on Cognitive Computational Neuroscience, September 2019 (conference)
ei
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
re
Xu, L., Wirzberger, M., Lieder, F.
How should we incentivize learning? An optimal feedback mechanism for educational games and online courses
41st Annual Meeting of the Cognitive Science Society, July 2019 (conference)
ei
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)
re
Mohnert, F., Pachur, T., Lieder, F.
What’s in the Adaptive Toolbox and How Do People Choose From It? Rational Models of Strategy Selection in Risky Choice
41st Annual Meeting of the Cognitive Science Society, July 2019 (conference)
re
Jain, Y. R., Callaway, F., Lieder, F.
Measuring how people learn how to plan
RLDM 2019, July 2019 (conference)
re
Jain, Y. R., Callaway, F., Lieder, F.
Measuring how people learn how to plan
41st Annual Meeting of the Cognitive Science Society, July 2019 (conference)
ei
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)
re
Lieder, F., Callaway, F., Jain, Y., Krueger, P., Das, P., Gul, S., Griffiths, T.
A cognitive tutor for helping people overcome present bias
RLDM 2019, July 2019 (conference)
ei
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)
ei
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)
ei
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)
ei
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)
ei
ps
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)
ei
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
re
Iwama, G., Greenberg, S., Moore, D., Lieder, F.
Introducing the Decision Advisor: A simple online tool that helps people overcome cognitive biases and experience less regret in real-life decisions
40th Annual Meeting of the Society for Judgement and Decision Making, June 2019 (conference)
ei
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)
re
Iwama, G. Y., Wirzberger, M., Lieder, F.
The Goal Characteristics (GC) questionannaire: A comprehensive measure for goals’ content, attainability, interestingness, and usefulness
40th Annual Meeting of the Society for Judgement and Decision Making, June 2019 (conference)
ei
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)
ei
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)
ei
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)
ei
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)
ei
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)
ei
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)
ei
pn
Schneider, F., Balles, L., Hennig, P.
DeepOBS: A Deep Learning Optimizer Benchmark Suite
7th International Conference on Learning Representations (ICLR), May 2019 (conference)
ei
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)
ei
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)
ei
Bauer, M., Mnih, A.
Resampled Priors for Variational Autoencoders
22nd International Conference on Artificial Intelligence and Statistics, April 2019 (conference) Accepted
ei
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)
ei
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)
ei
pn
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)
pn
ei
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)
ei
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)
ei
Mehrjou, A., Jitkrittum, W., Schölkopf, B., Muandet, K.
Witnessing Adversarial Training in Reproducing Kernel Hilbert Spaces
2019 (conference) Submitted
ei
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)
re
Mohnert, F., Tosic, M., Lieder, F.
Testing Computational Models of Goal Pursuit
2019 (conference)
ei
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
ei
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
re
Das, P., Callaway, F., Griffiths, T., Lieder, F.
Remediating cognitive decline with cognitive tutors
RLDM 2019, 2019 (conference)
ei
Kanagawa, H., Jitkrittum, W., Mackey, L., Fukumizu, K., Gretton, A.
A Kernel Stein Test for Comparing Latent Variable Models
2019 (conference) Submitted
ei
ps
Ghosh*, P., Sajjadi*, M. S. M., Vergari, A., Black, M. J., Schölkopf, B.
From Variational to Deterministic Autoencoders
2019, *equal contribution (conference) Submitted
ei
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
am
ei
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)
am
ei
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)
am
ei
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)
am
ei
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)
am
ei
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)
am
ei
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)