| Visualizing deep neural network decisions: Prediction difference analysis LM Zintgraf, TS Cohen, T Adel, M Welling The fifth International Conference on Learning Representations (ICLR 2017), 2017 | 397* | 2017 |
| Fast Context Adaptation via Meta-Learning LM Zintgraf, K Shiarlis, V Kurin, K Hofmann, S Whiteson Thirty-sixth International Conference on Machine Learning (ICML 2019), 2018 | 108* | 2018 |
| Deep Variational Reinforcement Learning for POMDPs M Igl, L Zintgraf, TA Le, F Wood, S Whiteson Thirty-fifth International Conference on Machine Learning (ICML 2018), 2018 | 95 | 2018 |
| VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning L Zintgraf, K Shiarlis, M Igl, S Schulze, Y Gal, K Hofmann, S Whiteson International Conference on Learning Representations (ICLR) 2020, 2019 | 33 | 2019 |
| Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making LM Zintgraf, DM Roijers, S Linders, CM Jonker, A Nowé 17th International Conference on Autonomous Agents and Multiagent Systems …, 2018 | 24 | 2018 |
| Quality assessment of MORL algorithms: A utility-based approach LM Zintgraf, TV Kanters, DM Roijers, F Oliehoek, P Beau Benelearn 2015: Proceedings of the 24th Annual Machine Learning Conference …, 2015 | 14 | 2015 |
| Interactive thompson sampling for multi-objective multi-armed bandits DM Roijers, LM Zintgraf, A Nowé International Conference on Algorithmic DecisionTheory, 18-34, 2017 | 13 | 2017 |
| Interpretation of microbiota-based diagnostics by explaining individual classifier decisions A Eck, LM Zintgraf, EFJ de Groot, TGJ de Meij, TS Cohen, PHM Savelkoul, ... BMC bioinformatics 18 (1), 1-13, 2017 | 10 | 2017 |
| Interactive multi-objective reinforcement learning in multi-armed bandits for any utility function DM Roijers, LM Zintgraf, P Libin, A Nowé ALA workshop at FAIM 8, 2018 | 5 | 2018 |
| Variational Task Embeddings for Fast Adaptation in Deep Reinforcement Learning L Zintgraf, M Igl, K Shiarlis, A Mahajan, K Hofmann, S Whiteson | 5* | |
| MORL-Glue: A benchmark suite for multi-objective reinforcement learning P Vamplew, D Webb, LM Zintgraf, DM Roijers, R Dazeley, R Issabekov, ... 29th Benelux Conference on Artificial Intelligence November 8–9, 2017 …, 2017 | 4 | 2017 |
| Varibad: a very good method for bayes-adaptive deep rl via meta-learning S Schulze, S Whiteson, L Zintgraf, M Igl, Y Gal, K Shiarlis, K Hofmann International Conference on Learning Representations, 2020 | 3 | 2020 |
| MultiMAuS: A Multi-Modal Authentication Simulator for Fraud Detection Research LM Zintgraf, EA Lopez-Rojas, DM Roijers, A Nowé The European Modeling and Simulation Symposium (EMSS) 2017, 2017 | 3 | 2017 |
| Deep Interactive Bayesian Reinforcement Learning via Meta-Learning L Zintgraf, S Devlin, K Ciosek, S Whiteson, K Hofmann arXiv preprint arXiv:2101.03864, 2021 | | 2021 |
| Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning L Zintgraf, L Feng, M Igl, K Hartikainen, K Hofmann, S Whiteson arXiv preprint arXiv:2010.01062, 2020 | | 2020 |
| VIABLE: Fast Adaptation via Backpropagating Learned Loss L Feng, L Zintgraf, B Peng, S Whiteson arXiv preprint arXiv:1911.13159, 2019 | | 2019 |
| Interactive Multi-Objective Reinforcement Learning in Multi-Armed Bandits with Gaussian Process Utility Models DM Roijers, LM Zintgraf, P Libin, M Reymond, E Bargiacchi, A Nowé | | |
Shimon WhitesonProfessor of Computer Science, University of Oxford / Head of Research, Waymo UKBestätigte E-Mail-Adresse bei cs.ox.ac.uk
