| 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 | 943* | 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 | 471 | 2018 |
| A practical guide to multi-objective reinforcement learning and planning CF Hayes, R Rădulescu, E Bargiacchi, J Källström, M Macfarlane, ... Autonomous Agents and Multi-Agent Systems 36 (1), 26, 2022 | 358 | 2022 |
| 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 | 330 | 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 | 296 | 2019 |
| A survey of meta-reinforcement learning J Beck, R Vuorio, EZ Liu, Z Xiong, L Zintgraf, C Finn, S Whiteson arXiv preprint arXiv:2301.08028, 2023 | 152 | 2023 |
| 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 | 77 | 2018 |
| Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning L Zintgraf, L Feng, C Lu, M Igl, K Hartikainen, K Hofmann, S Whiteson International Conference on Machine Learning (ICML) 2021, 2020 | 55 | 2020 |
| Orbit: A real-world few-shot dataset for teachable object recognition D Massiceti, L Zintgraf, J Bronskill, L Theodorou, MT Harris, E Cutrell, ... Proceedings of the IEEE/CVF International Conference on Computer Vision
, 2021 | 51 | 2021 |
| Varibad: Variational bayes-adaptive deep rl via meta-learning L Zintgraf, S Schulze, C Lu, L Feng, M Igl, K Shiarlis, Y Gal, K Hofmann, ... Journal of Machine Learning Research 22 (289), 1-39, 2021 | 49 | 2021 |
| Deep Interactive Bayesian Reinforcement Learning via Meta-Learning L Zintgraf, S Devlin, K Ciosek, S Whiteson, K Hofmann AAMAS 2021 (Extended Abstract), 2021 | 45 | 2021 |
| Prospect pruning: Finding trainable weights at initialization using meta-gradients M Alizadeh, SA Tailor, LM Zintgraf, J van Amersfoort, S Farquhar, ... International Conference on Learning Representations (ICLR) 2022, 2022 | 44 | 2022 |
| 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 | 44 | 2015 |
| Interactive thompson sampling for multi-objective multi-armed bandits DM Roijers, LM Zintgraf, A Nowé Algorithmic Decision Theory: 5th International Conference, ADT 2017
, 2017 | 41 | 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, 1-13, 2017 | 37 | 2017 |
| Disability-first dataset creation: lessons from constructing a dataset for teachable object recognition with blind and low vision data collectors L Theodorou, D Massiceti, L Zintgraf, S Stumpf, C Morrison, E Cutrell, ... Proceedings of the 23rd International ACM SIGACCESS Conference on Computers
, 2021 | 34 | 2021 |
| 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 | 16 | 2018 |
| On the practical consistency of meta-reinforcement learning algorithms Z Xiong, L Zintgraf, J Beck, R Vuorio, S Whiteson arXiv preprint arXiv:2112.00478, 2021 | 12 | 2021 |
| 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 Machine Learning and Knowledge Discovery in Databases: European Conference
, 2021 | 11 | 2021 |
| 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 89, 2017
, 2017 | 10 | 2017 |
Shimon WhitesonProfessor of Computer Science, University of Oxford / Senior Staff Research Scientist, WaymoPatvirtintas el. paštas cs.ox.ac.uk
