Sajjadi, M. S. M., Vemulapalli, R., Brown, M. Frame-Recurrent Video Super-Resolution IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018 (conference)

ArXiv link (url) [BibTex]

Jin, M., Hirsch, M., Favaro, P. Learning Face Deblurring Fast and Wide The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages: 745-753, June 2018 (conference)

link (url) [BibTex]

Tolstikhin, I., Bousquet, O., Gelly, S., Schölkopf, B. Wasserstein Auto-Encoders 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) Project Page [BibTex]

Dehghani, M., Mehrjou, A., Gouws, S., Kamps, J., Schölkopf, B. Fidelity-Weighted Learning 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) Project Page [BibTex]

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]

Ewerton, M., Rother, D., Weimar, J., Kollegger, G., Wiemeyer, J., Peters, J., Maeda, G. Assisting Movement Training and Execution With Visual and Haptic Feedback Frontiers in Neurorobotics, 12, May 2018 (article)

DOI 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]

Manschitz, S., Gienger, M., Kober, J., Peters, J. Mixture of Attractors: A Novel Movement Primitive Representation for Learning Motor Skills From Demonstrations IEEE Robotics and Automation Letters, 3(2):926-933, April 2018 (article)

DOI Project Page [BibTex]

Paraschos, A., Rueckert, E., Peters, J., Neumann, G. Probabilistic movement primitives under unknown system dynamics Advanced Robotics, 32(6):297-310, April 2018 (article)

DOI 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]

Osa, T., Pajarinen, J., Neumann, G., Bagnell, J., Abbeel, P., Peters, J. An Algorithmic Perspective on Imitation Learning Foundations and Trends in Robotics, 7(1-2):1-179, March 2018 (article)

DOI Project Page [BibTex]

Paraschos, A., Daniel, C., Peters, J., Neumann, G. Using Probabilistic Movement Primitives in Robotics Autonomous Robots, 42(3):529-551, March 2018 (article)

DOI Project Page [BibTex]

Goris, R., Henaff, O., Meding, K. Representation of sensory uncertainty in macaque visual cortex Computational and Systems Neuroscience (COSYNE) 2018, March 2018 (poster)

[BibTex]

Kroemer, O., Leischnig, S., Luettgen, S., Peters, J. A kernel-based approach to learning contact distributions for robot manipulation tasks Autonomous Robots, 42(3):581-600, March 2018 (article)

DOI Project Page [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]

Vinogradska, J., Bischoff, B., Peters, J. Approximate Value Iteration Based on Numerical Quadrature IEEE Robotics and Automation Letters, 3(2):1330-1337, January 2018 (article)

DOI Project Page [BibTex]

Yi, Z., Zhang, Y., Peters, J. Biomimetic Tactile Sensors and Signal Processing with Spike Trains: A Review Sensors and Actuators A: Physical, 269, pages: 41-52, January 2018 (article)

DOI Project Page [BibTex]

Napieczynska, H., Kolb, A., Katiyar, P., Tonietto, M., Ud-Dean, M., Stumm, R., Herfert, K., Calaminus, C., Pichler, B. Impact of the AIF Recording Method on Kinetic Parameters in Small Animal PET Journal of Nuclear Medicine, 2018 (article)

DOI [BibTex]

Schölkopf, B. Die kybernetische Revolution 15-Mar-2018, Süddeutsche Zeitung, 2018 (misc)

link (url) [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]

Damanet, F., Kübler, J. M., Martin, J., Braun, D. Nonclassical states of light with a smooth P function Physical Review A, 97(2):023832, 2018 (article)

link (url) DOI [BibTex]

Shah*, N., Tabibian*, B., Muandet, K., Guyon, I., von Luxburg, U. Design and Analysis of the NIPS 2016 Review Process Journal of Machine Learning Research, 19(49):1-34, 2018, *equal contribution (article)

arXiv link (url) Project Page Project Page [BibTex]

Tanneberg, D., Peters, J., Rueckert, E. Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks Neural Networks, 109, pages: 67-80, 2018 (article)

link (url) DOI Project Page [BibTex]

Zafar, M. B., Valera, I., Gomez Rodriguez, M., Gummadi, K. A Flexible Approach for Fair Classification Journal of Machine Learning, 2018 (article) Accepted

Project Page [BibTex]

Gomez-Gonzalez, S., Neumann, G., Schölkopf, B., Peters, J. Adaptation and Robust Learning of Probabilistic Movement Primitives IEEE Transactions on Robotics, 2018 (article) In revision

arXiv 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]

Janzing, D., Wocjan, P. Does universal controllability of physical systems prohibit thermodynamic cycles? Open Systems and Information Dynamics, 25(3):1850016, 2018 (article)

PDF DOI [BibTex]

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

[BibTex]

Haider, S., Yao, C., Sabine, V., Grzadkowski, M., Stimper, V., Starmans, M., Wang, J., Nguyen, F., Moon, N., Lin, X., Drake, C., Crozier, C., Brookes, C., van de Velde, C., Hasenburg, A., Kieback, D., Markopoulos, C., Dirix, L., Seynaeve, C., Rea, D., Kasprzyk, A., Lambin, P., Lio’, P., Bartlett, J., Boutros, P. Pathway-based subnetworks enable cross-disease biomarker discovery Nature Communications, 9, 2018, Article number: 4746 (article)

link (url) DOI [BibTex]

Zhang, K., Schölkopf, B., Spirtes, P., Glymour, C. Learning Causality and Causality-Related Learning: Some Recent Progress National Science Review, 5(1):26-29, 2018 (article)

DOI [BibTex]

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

[BibTex]

Koc, O., Maeda, G., Peters, J. Online optimal trajectory generation for robot table tennis Robotics and Autonomous Systems, 105, pages: 121-137, 2018 (article)

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Pfister*, N., Weichwald*, S., Bülmann, P., Schölkopf, B. Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise 2018, *equal contribution (article) Submitted

ArXiv Code Project page PDF Project Page Project Page [BibTex]

Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S. Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference Arxiv e-prints, arXiv:1805.08845v1 [stat.ML], 2018 (article)

arXiv [BibTex]

Osa, T., Peters, J., Neumann, G. Hierarchical Reinforcement Learning of Multiple Grasping Strategies with Human Instructions Advanced Robotics, 32(18):955-968, 2018 (article)

DOI Project Page [BibTex]

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

[BibTex]