Luisa M Zintgraf
Luisa M Zintgraf
Verified email at cs.ox.ac.uk
TitleCited byYear
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
246*2017
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
432018
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
31*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
132015
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
102018
Interactive thompson sampling for multi-objective multi-armed bandits
DM Roijers, LM Zintgraf, A Nowé
International Conference on Algorithmic DecisionTheory, 18-34, 2017
102017
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
42018
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), 441, 2017
42017
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
32017
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
32017
Variational Task Embeddings for Fast Adaptation in Deep Reinforcement Learning
L Zintgraf, M Igl, K Shiarlis, A Mahajan, K Hofmann, S Whiteson
2*
VIABLE: Fast Adaptation via Backpropagating Learned Loss
L Feng, L Zintgraf, B Peng, S Whiteson
arXiv preprint arXiv:1911.13159, 2019
2019
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
2019
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Articles 1–13