| Generative adversarial active learning JJ Zhu, J Bento arXiv preprint arXiv:1702.07956, 2017 | 185 | 2017 |
| Deep reinforcement learning for event-triggered control D Baumann, JJ Zhu, G Martius, S Trimpe 2018 IEEE Conference on Decision and Control (CDC), 943-950, 2018 | 57 | 2018 |
| Kernel distributionally robust optimization: Generalized duality theorem and stochastic approximation JJ Zhu, W Jitkrittum, M Diehl, B Schölkopf International Conference on Artificial Intelligence and Statistics, 280-288, 2021 | 39* | 2021 |
| Control What You Can: Intrinsically Motivated Task-Planning Agent S Blaes, MV Pogančić, JJ Zhu, G Martius Advances in Neural Information Processing Systems, 2019, 2019 | 33 | 2019 |
| Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning* MH Yeganegi, M Khadiv, SAA Moosavian, JJ Zhu, A Del Prete, L Righetti 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids …, 2019 | 17 | 2019 |
| Projection algorithms for nonconvex minimization with application to sparse principal component analysis WW Hager, DT Phan, JJ Zhu Journal of Global Optimization 65 (4), 657-676, 2016 | 17 | 2016 |
| A metric for sets of trajectories that is practical and mathematically consistent J Bento, JJ Zhu arXiv preprint arXiv:1601.03094, 2016 | 17 | 2016 |
| Worst-Case Risk Quantification under Distributional Ambiguity using Kernel Mean Embedding in Moment Problem JJ Zhu, W Jitkrittum, M Diehl, B Schölkopf 2020 59th IEEE Conference on Decision and Control (CDC), 3457-3463, 2020 | 14 | 2020 |
| Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Hybrid Model Predictive Control JJ Zhu, G Martius IFAC-PapersOnLine 53 (2), 5239-5245, 2020 | 14* | 2020 |
| Functional generalized empirical likelihood estimation for conditional moment restrictions H Kremer, JJ Zhu, K Muandet, B Schölkopf International Conference on Machine Learning, 11665-11682, 2022 | 7 | 2022 |
| A new distribution-free concept for representing, comparing, and propagating uncertainty in dynamical systems with kernel probabilistic programming JJ Zhu, K Muandet, M Diehl, B Schölkopf IFAC-PapersOnLine 53 (2), 7240-7247, 2020 | 7 | 2020 |
| A Kernel Mean Embedding Approach to Reducing Conservativeness in Stochastic Programming and Control JJ Zhu, M Diehl, B Schölkopf Proceedings of the 2nd Conference on Learning for Dynamics and Control …, 2020 | 7 | 2020 |
| Maximum mean discrepancy distributionally robust nonlinear chance-constrained optimization with finite-sample guarantee Y Nemmour, H Kremer, B Schölkopf, JJ Zhu 2022 IEEE 61st Conference on Decision and Control (CDC), 5660-5667, 2022 | 6 | 2022 |
| Adversarially Robust Kernel Smoothing JJ Zhu, C Kouridi, Y Nemmour, B Schölkopf arXiv preprint arXiv:2102.08474, 2021 | 6 | 2021 |
| A decentralized multi-block ADMM for demand-side primary frequency control using local frequency measurements J Brooks, W Hager, J Zhu arXiv preprint arXiv:1509.08206, 2015 | 5 | 2015 |
| Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative Entropy Trust-Regions H Abdulsamad, T Dorau, B Belousov, JJ Zhu, J Peters arXiv preprint arXiv:2103.15388, 2021 | 4 | 2021 |
| Distributional Robustness Regularized Scenario Optimization with Application to Model Predictive Control Y Nemmour, B Schölkopf, JJ Zhu arXiv preprint arXiv:2110.13588, 2021 | 3* | 2021 |
| Nonlinear Wasserstein Distributionally Robust Optimal Control Z Zhong, JJ Zhu arXiv preprint arXiv:2304.07415, 2023 | 2 | 2023 |
| A Mini-Course on Optimization and Dynamics: from Euclidean Gradient Descent to Wasserstein Gradient Flow JJ Zhu | | 2023 |
| Estimation Beyond Data Reweighting: Kernel Method of Moments H Kremer, Y Nemmour, B Schölkopf, JJ Zhu arXiv preprint arXiv:2305.10898, 2023 | | 2023 |
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
