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
von Kügelgen, J., Mey, A., Loog, M., Schölkopf, B.
Semi-supervised learning, causality, and the conditional cluster assumption
NeurIPS 2019 Workshop “Do the right thing”: machine learning and causal inference for improved decision making, December 2019 (poster) Accepted
ei
von Kügelgen, J., Rubenstein, P., Schölkopf, B., Weller, A.
Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
NeurIPS 2019 Workshop “Do the right thing”: machine learning and causal inference for improved decision making, December 2019 (poster) Accepted
dlg
ics
Heim, S., Rohr, A. V., Trimpe, S., Badri-Spröwitz, A.
A Learnable Safety Measure
Conference on Robot Learning, November 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
dlg
Drama, Ö., Badri-Spröwitz, A.
Trunk Pitch Oscillations for Joint Load Redistribution in Humans and Humanoid Robots
Proceedings International Conference on Humanoid Robots, Humanoids, September 2019 (conference) Accepted
ei
Gebhard, T., Kilbertus, N., Harry, I., Schölkopf, B.
Convolutional neural networks: A magic bullet for gravitational-wave detection?
Physical Review D, 100(6):063015, American Physical Society, September 2019 (article)
ei
Babbar, R., Schölkopf, B.
Data scarcity, robustness and extreme multi-label classification
Machine Learning, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (article)
dlg
Ruppert, F., Badri-Spröwitz, A.
Series Elastic Behavior of Biarticular Muscle-Tendon Structure in a Robotic Leg
Frontiers in Neurorobotics, 64, pages: 13, 13, August 2019 (article)
dlg
Heim, S., Millard, M., Le Mouel, C., Sproewitz, A.
The positive side of damping
Proceedings of AMAM, The 9th International Symposium on Adaptive Motion of Animals and Machines, August 2019 (conference) Accepted
dlg
Steve Heim, , Spröwitz, A.
Beyond Basins of Attraction: Quantifying Robustness of Natural Dynamics
IEEE Transactions on Robotics (T-RO) , 35(4), pages: 939-952, August 2019 (article)
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
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)
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)
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
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)
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)
am
Kloss, A., Bauza, M., Wu, J., Tenenbaum, J. B., Rodriguez, A., Bohg, J.
Accurate Vision-based Manipulation through Contact Reasoning
In International Conference on Robotics and Automation, May 2019 (inproceedings) Submitted
am
Sutanto, G., Ratliff, N., Sundaralingam, B., Chebotar, Y., Su, Z., Handa, A., Fox, D.
Learning Latent Space Dynamics for Tactile Servoing
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2019, IEEE, International Conference on Robotics and Automation, May 2019 (inproceedings) Accepted
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)
mms
pi
Sanli, U., Baluktsian, M., Ceylan, H., Sitti, M., Weigand, M., Schütz, G., Keskinbora, K.
X-ray Optics Fabrication Using Unorthodox Approaches
Bulletin of the American Physical Society, APS, 2019 (article)
ei
Rojas-Carulla, M.
Learning Transferable Representations
University of Cambridge, UK, 2019 (phdthesis)
ei
Gu, S.
Sample-efficient deep reinforcement learning for continuous control
University of Cambridge, UK, 2019 (phdthesis)
mms
Gross, F., Träger, N., Förster, J., Weigand, M., Schütz, G., Gräfe, J.
Nanoscale detection of spin wave deflection angles in permalloy
{Applied Physics Letters}, 114(1), American Institute of Physics, Melville, NY, 2019 (article)
ei
Aghaeifar, A., Zhou, J., Heule, R., Tabibian, B., Schölkopf, B., Jia, F., Zaitsev, M., Scheffler, K.
A 32-channel multi-coil setup optimized for human brain shimming at 9.4T
Magnetic Resonance in Medicine, 2019, (Early View) (article)
mms
Yu, P., Li, J., Li, X., Schütz, G., Hirscher, M., Zhang, S., Liu, N.
Generation of switchable singular beams with dynamic metasurfaces
{ACS Nano}, 13(6):7100-7106, American Chemical Society, Washington, DC, 2019 (article)
mms
Schaffers, T., Feggeler, T., Pile, S., Meckenstock, R., Buchner, M., Spoddig, D., Ney, V., Farle, M., Wende, H., Wintz, S., Weigand, M., Ohldag, H., Ollefs, K, Ney, A.
Extracting the dynamic magnetic contrast in time-resolved X-ray transmission microscopy
{Nanomaterials}, 9(7), MDPI, Basel, Schweiz, 2019 (article)
ei
Lim, J. N., Yamada, M., Jitkrittum, W., Terada, Y., Matsui, S., Shimodaira, H.
More Powerful Selective Kernel Tests for Feature Selection
2019 (misc) Submitted
mms
Groß, F., Mart\’\inez-Garc\’\ia, J. C., Ilse, S. E., Schütz, G., Goering, E., Rivas, M., Gräfe, J.
gFORC: A graphics processing unit accelerated first-order reversal-curve calculator
{Journal of Applied Physics}, 126(16), AIP Publishing, New York, NY, 2019 (article)
mms
Filianina, M., Baldrati, L., Hajiri, T., Litzius, K., Foerster, M., Aballe, L., Kläui, M.
Piezo-electrical control of gyration dynamics of magnetic vortices
{Applied Physics Letters}, 115(6), American Institute of Physics, Melville, NY, 2019 (article)
ei
Stimper, V., Bauer, S., Ernstorfer, R., Schölkopf, B., Xian, R. P.
Multidimensional Contrast Limited Adaptive Histogram Equalization
IEEE Access, 7, pages: 165437-165447, 2019 (article)