Lioutikov, R., Maeda, G., Veiga, F., Kersting, K., Peters, J. Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives IEEE International Conference on Robotics and Automation, (ICRA), pages: 1-8, IEEE, May 2018 (conference)

DOI Project Page [BibTex]

Mroueh, Y., Li*, C., Sercu*, T., Raj*, A., Cheng, Y. Sobolev GAN 6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

link (url) Project Page [BibTex]

Pong*, V., Gu*, S., Dalal, M., Levine, S. Temporal Difference Models: Model-Free Deep RL for Model-Based Control 6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

link (url) Project Page [BibTex]

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I. Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) Project Page [BibTex]

Eysenbach, B., Gu, S., Ibarz, J., Levine, S. Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

Videos link (url) Project Page [BibTex]

Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B. Tempered Adversarial Networks Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

arXiv [BibTex]

Koert, D., Maeda, G., Neumann, G., Peters, J. Learning Coupled Forward-Inverse Models with Combined Prediction Errors IEEE International Conference on Robotics and Automation, (ICRA), pages: 2433-2439, IEEE, May 2018 (conference)

DOI Project Page [BibTex]

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I. Learning Disentangled Representations with Wasserstein Auto-Encoders Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) Project Page [BibTex]

Bauer, M., Volchkov, V., Hirsch, M., Schölkopf, B. Automatic Estimation of Modulation Transfer Functions IEEE International Conference on Computational Photography (ICCP), May 2018 (conference)

DOI [BibTex]

Rojas-Carulla, M., Baroni, M., Lopez-Paz, D. Causal Discovery Using Proxy Variables Workshop at 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) [BibTex]

Pinsler, R., Akrour, R., Osa, T., Peters, J., Neumann, G. Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences IEEE International Conference on Robotics and Automation, (ICRA), pages: 596-601, IEEE, May 2018 (conference)

DOI Project Page [BibTex]

Besserve, M., Shajarisales, N., Schölkopf, B., Janzing, D. Group invariance principles for causal generative models Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 557-565, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

link (url) [BibTex]

Locatello, F., Khanna, R., Ghosh, J., Rätsch, G. Boosting Variational Inference: an Optimization Perspective Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 464-472, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

link (url) Project Page Project Page [BibTex]

Blöbaum, P., Janzing, D., Washio, T., Shimizu, S., Schölkopf, B. Cause-Effect Inference by Comparing Regression Errors Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) , 84, pages: 900-909, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

link (url) [BibTex]

Schwarz, K., Wieschollek, P., Lensch, H. P. A. Will People Like Your Image? Learning the Aesthetic Space 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pages: 2048-2057, March 2018 (conference)

DOI [BibTex]

Kim, J., Tabibian, B., Oh, A., Schölkopf, B., Gomez Rodriguez, M. Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), pages: 324-332, (Editors: Yi Chang, Chengxiang Zhai, Yan Liu, and Yoelle Maarek), ACM, Febuary 2018 (conference)

DOI Project Page Project Page [BibTex]

Ścibior, A., Kammar, O., Ghahramani, Z. Functional Programming for Modular Bayesian Inference Proceedings of the ACM on Functional Programming (ICFP), 2(Article No. 83):1-29, ACM, 2018 (conference)

DOI Project Page [BibTex]

Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I. Automatic Bayesian Density Analysis 2018 (conference) Submitted

arXiv [BibTex]

Bustamante, S. A virtual reality environment for experiments in assistive robotics and neural interfaces Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

PDF [BibTex]

Kilcher*, Y., Becigneul*, G., Hofmann, T. Magic Tunnels ICLR 2019, 2018, *equal contribution (conference) Submitted

[BibTex]

Koc, O. Optimal Trajectory Generation and Learning Control for Robot Table Tennis Technical University Darmstadt, Germany, 2018 (phdthesis)

[BibTex]

Babbar, R., Schölkopf, B. Adversarial Extreme Multi-label Classification 2018 (conference) Submitted

[BibTex]

Raj, A., Stich, S. k–SVRG: Variance Reduction for Large Scale Optimization In 2018 (inproceedings) Submitted

[BibTex]

Gebhard, T. On the Applicability of Machine Learning to Aid the Search for Gravitational Waves at the LIGO Experiment Karlsruhe Institute of Technology, Germany, 2018 (mastersthesis)

[BibTex]

Simon-Gabriel, C. J. Distribution-Dissimilarities in Machine Learning Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

[BibTex]

Peharz, R., Vergari, A., Stelzner, K., Molina, A., Trapp, M., Kersting, K., Ghahramani, Z. Probabilistic Deep Learning using Random Sum-Product Networks 2018 (conference) Submitted

arXiv [BibTex]

Lechner, T. Domain Adaptation Under Causal Assumptions Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

[BibTex]

Raj*, A., Law*, L., Sejdinovic*, D., Park, M. A Differentially Private Kernel Two-Sample Test 2018, *equal contribution (conference) Submitted

[BibTex]

Suter, R. A Causal Perspective on Deep Representation Learning ETH Zurich, 2018 (mastersthesis)

[BibTex]

Besserve, M., Sun, R., Schölkopf, B. Counterfactuals uncover the modular structure of deep generative models 2018 (conference) Submitted

[BibTex]

Becigneul, G., Ganea, O. Riemannian Adaptive Optimization Methods ICLR 2019, 2018 (conference) Submitted

[BibTex]

Mahsereci, M. Probabilistic Approaches to Stochastic Optimization Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

link (url) Project Page [BibTex]

Zabel, S. Improving Tissue Differentiation based on Optical Emission Spectroscopy for Guided Electrosurgical Tumor Resection with Machine Learning Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

[BibTex]

Guist, S. Reinforcement Learning for High-Speed Robotics with Muscular Actuation Ruprecht-Karls-Universität Heidelberg , 2018 (mastersthesis)

[BibTex]

Ścibior, A., Kammar, O., Vákár, M., Staton, S., Yang, H., Cai, Y., Ostermann, K., Moss, S. K., Heunen, C., Ghahramani, Z. Denotational Validation of Higher-order Bayesian Inference Proceedings of the ACM on Principles of Programming Languages (POPL), 2(Article No. 60):1-29, ACM, 2018 (conference)

DOI Project Page [BibTex]

Tifrea*, A., Becigneul*, G., Ganea*, O. Poincaré GloVe: Hyperbolic Word Embeddings ICLR 2019, 2018, *equal contribution (conference) Submitted

[BibTex]

Schober, M. Probabilistic Ordinary Differential Equation Solvers — Theory and Applications Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

[BibTex]

Jayaram, V. A machine learning approach to taking EEG-based computer interfaces out of the lab Graduate Training Centre of Neuroscience, IMPRS, Eberhard Karls Universität Tübingen, Germany, 2018 (phdthesis)

[BibTex]

Schober, M. Camera-specific Image Denoising Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

PDF [BibTex]

Logothetis, N., Eschenko, O., Murayama, Y., Augath, M., Steudel, T., Evrard, H., Besserve, M., Oeltermann, A. Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience}, year = {2013}, month = {7}, volume = {14}, number = {Supplement 1}, pages = {A1}, (talk)

Web [BibTex]

Balduzzi, D. Falsification and future performance In Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 7070, pages: 65-78, Lecture Notes in Computer Science, Springer, Berlin, Germany, Solomonoff 85th Memorial Conference, January 2013 (inproceedings)

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Gopalan, N., Deisenroth, M., Peters, J. Feedback Error Learning for Rhythmic Motor Primitives In Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA 2013), pages: 1317-1322, 2013 (inproceedings)

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Lopez-Paz, D., Hernandez-Lobato, J., Ghahramani, Z. Gaussian Process Vine Copulas for Multivariate Dependence In Proceedings of the 30th International Conference on Machine Learning, W&CP 28(2), pages: 10-18, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013, Poster: http://people.tuebingen.mpg.de/dlopez/papers/icml2013_gpvine_poster.pdf (inproceedings)

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Lopez-Paz, D., Hennig, P., Schölkopf, B. The Randomized Dependence Coefficient In Advances in Neural Information Processing Systems 26, pages: 1-9, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

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Harmeling, S., Hirsch, M., Schölkopf, B. On a link between kernel mean maps and Fraunhofer diffraction, with an application to super-resolution beyond the diffraction limit In IEEE Conference on Computer Vision and Pattern Recognition, pages: 1083-1090, IEEE, CVPR, 2013 (inproceedings)

DOI [BibTex]

Dinuzzo, F., Ong, C., Fukumizu, K. Output Kernel Learning Methods In International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications, ROKS, 2013 (inproceedings)

[BibTex]

Bocsi, B., Csato, L., Peters, J. Alignment-based Transfer Learning for Robot Models In Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN 2013), pages: 1-7, 2013 (inproceedings)

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Chen, Z., Zhang, K., Chan, L. Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method In 13th International Conference on Data Mining, pages: 1003-1008, (Editors: H. Xiong, G. Karypis, B. M. Thuraisingham, D. J. Cook and X. Wu), IEEE Computer Society, ICDM, 2013 (inproceedings)

DOI [BibTex]

Paraschos, A., Neumann, G., Peters, J. A probabilistic approach to robot trajectory generation In Proceedings of the 13th IEEE International Conference on Humanoid Robots (HUMANOIDS), pages: 477-483, IEEE, 13th IEEE-RAS International Conference on Humanoid Robots, 2013 (inproceedings)

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Sra, S., Hosseini, R. Geometric optimisation on positive definite matrices for elliptically contoured distributions In Advances in Neural Information Processing Systems 26, pages: 2562-2570, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

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