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
Hill, J., Lal, T., Bierig, K., Birbaumer, N., Schölkopf, B.
Attentional Modulation of Auditory Event-Related Potentials in a Brain-Computer Interface
In BioCAS04, (S3/5/INV- S3/17-20):4, IEEE Computer Society, Los Alamitos, CA, USA, 2004 IEEE International Workshop on Biomedical Circuits and Systems, December 2004 (inproceedings)
Honkela, A., Harmeling, S., Lundqvist, L., Valpola, H.
Using kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method
In ICA 2004, pages: 790-797, (Editors: Puntonet, C. G., A. Prieto), Springer, Berlin, Germany, Fifth International Conference on Independent Component Analysis and Blind Signal Separation, October 2004 (inproceedings)
Meinecke, F., Harmeling, S., Müller, K.
Robust ICA for Super-Gaussian Sources
In ICA 2004, pages: 217-224, (Editors: Puntonet, C. G., A. Prieto), Springer, Berlin, Germany, Fifth International Conference on Independent Component Analysis and Blind Signal Separation, October 2004 (inproceedings)
Görür, D., Rasmussen, C., Tolias, A., Sinz, F., Logothetis, N.
Modelling Spikes with Mixtures of Factor Analysers
In Pattern Recognition, pages: 391-398, LNCS 3175, (Editors: Rasmussen, C. E. , H.H. Bülthoff, B. Schölkopf, M.A. Giese), Springer, Berlin, Germany, 26th DAGM Symposium, September 2004 (inproceedings)
Sinz, F., Candela, J., BakIr, G., Rasmussen, C., Franz, M.
Learning Depth From Stereo
In 26th DAGM Symposium, pages: 245-252, LNCS 3175, (Editors: Rasmussen, C. E., H. H. Bülthoff, B. Schölkopf, M. A. Giese), Springer, Berlin, Germany, 26th DAGM Symposium, September 2004 (inproceedings)
Shapiro, MD., Blaschko, MB.
Stability of Hausdorff-based Distance Measures
In VIIP, pages: 1-6, VIIP, September 2004 (inproceedings)
Schölkopf, B., Tsuda, K., Vert, J.
Kernel Methods in Computational Biology
pages: 410, Computational Molecular Biology, MIT Press, Cambridge, MA, USA, August 2004 (book)
BakIr, G., Zien, A., Tsuda, K.
Learning to Find Graph Pre-Images
In Pattern Recognition, pages: 253-261, (Editors: Rasmussen, C. E., H. H. Bülthoff, B. Schölkopf, M. A. Giese), Springer, Berlin, Germany, 26th DAGM Symposium, August 2004 (inproceedings)
Altun, Y., Hofmann, T., Smola, A.
Gaussian Process Classification for Segmenting and Annotating Sequences
In Proceedings of the 21st International Conference on Machine Learning (ICML 2004), pages: 25-32, (Editors: Greiner, R. , D. Schuurmans), ACM Press, New York, USA, 21st International Conference on Machine Learning (ICML), July 2004 (inproceedings)
Ong, CS., Mary, X., Canu, S., Smola, AJ.
Learning with Non-Positive Kernels
In ICML 2004, pages: 81-81, ACM Press, New York, NY, USA, Twenty-First International Conference on Machine Learning, July 2004 (inproceedings)
Altun, Y., Smola, A., Hofmann, T.
Exponential Families for Conditional Random Fields
In Proceedings of the 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2004), pages: 2-9, (Editors: Chickering, D.M. , J.Y. Halpern), Morgan Kaufmann, San Francisco, CA, USA, 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI), July 2004 (inproceedings)
Gregory, M., Altun, Y.
Using Conditional Random Fields to Predict Pitch Accent in Conversational Speech
In pages: 677-684, (Editors: Scott, D. , W. Daelemans, M. Walker), ACL, East Stroudsburg, PA, USA, 42nd Annual Meeting of the Association for Computational Linguistics (ACL), July 2004 (inproceedings)
Tsochantaridis, I., Hofmann, T., Joachims, T., Altun, Y.
Support vector machine learning for interdependent and structured output spaces
In pages: 1-8, (Editors: Greiner, R. , D. Schuurmans), AAAI Press, Menlo Park, CA, USA, Twenty-first International Conference on Machine Learning (ICML), July 2004 (inproceedings)
Audibert, J., Bousquet, O.
PAC-Bayesian Generic Chaining
In Advances in Neural Information Processing Systems 16, pages: 1125-1132 , (Editors: Thrun, S., L.K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)
Eichhorn, J., Tolias, A., Zien, A., Kuss, M., Rasmussen, C., Weston, J., Logothetis, N., Schölkopf, B.
Prediction on Spike Data Using Kernel Algorithms
In Advances in Neural Information Processing Systems 16, pages: 1367-1374, (Editors: S Thrun and LK Saul and B Schölkopf), MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)
Snelson, E., Rasmussen, CE., Ghahramani, Z.
Warped Gaussian Processes
In Advances in Neural Information Processing Systems 16, pages: 337-344, (Editors: Thrun, S., L.K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)