Luisa M. Zintgraf

41 papers A* 9A 4Journal 25Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Tutorial on Meta-Reinforcement Learning. Found. Trends Mach. Learn. Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson
2025	J	`jnl`	DataRater: Meta-Learned Dataset Curation. CoRR Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa M. Zintgraf, Matteo Hessel, Jeremy Shar, Junhyuk Oh, András György, Tom Schaul, Jeffrey Dean, Hado van Hasselt, David Silver
2025	J	`jnl`	Discovering state-of-the-art reinforcement learning algorithms. Nat. Junhyuk Oh, Gregory Farquhar, Iurii Kemaev, Dan A. Calian, Matteo Hessel, Luisa M. Zintgraf, Satinder Singh, Hado van Hasselt, David Silver
2025	A*	`conf`	Scalable Meta-Learning via Mixed-Mode Differentiation. ICML Iurii Kemaev, Dan A. Calian, Luisa M. Zintgraf, Gregory Farquhar, Hado van Hasselt
2025	J	`jnl`	Scalable Meta-Learning via Mixed-Mode Differentiation. CoRR Iurii Kemaev, Dan A. Calian, Luisa M. Zintgraf, Gregory Farquhar, Hado van Hasselt
2023	A	`conf`	A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2023	J	`jnl`	A Survey of Meta-Reinforcement Learning. CoRR Jacob Beck, Risto Vuorio, Evan Zheran Liu, Zheng Xiong, Luisa M. Zintgraf, Chelsea Finn, Shimon Whiteson
2022	J	`jnl`	A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2022	A*	`conf`	Communicating via Markov Decision Processes. ICML Samuel Sokota, Christian A. Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Martin Strohmeier, J. Zico Kolter, Shimon Whiteson, Jakob N. Foerster
2022	A*	`conf`	Generalized Beliefs for Cooperative AI. ICML Darius Muglich, Luisa M. Zintgraf, Christian A. Schröder de Witt, Shimon Whiteson, Jakob N. Foerster
2022	J	`jnl`	Generalized Beliefs for Cooperative AI. CoRR Darius Muglich, Luisa M. Zintgraf, Christian Schröder de Witt, Shimon Whiteson, Jakob N. Foerster
2022	A*	`conf`	Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients. ICLR Milad Alizadeh, Shyam A. Tailor, Luisa M. Zintgraf, Joost van Amersfoort, Sebastian Farquhar, Nicholas Donald Lane, Yarin Gal
2022	J	`jnl`	Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients. CoRR Milad Alizadeh, Shyam A. Tailor, Luisa M. Zintgraf, Joost van Amersfoort, Sebastian Farquhar, Nicholas Donald Lane, Yarin Gal
2021	J	`jnl`	A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2021	J	`jnl`	A Self-Supervised Auxiliary Loss for Deep RL in Partially Observable Settings. CoRR Eltayeb Ahmed, Luisa M. Zintgraf, Christian A. Schröder de Witt, Nicolas Usunier
2021	A	`conf`	Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. AAMAS Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
2021	J	`jnl`	Deep Interactive Bayesian Reinforcement Learning via Meta-Learning. CoRR Luisa M. Zintgraf, Sam Devlin, Kamil Ciosek, Shimon Whiteson, Katja Hofmann
2021	A	`conf`	Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors. ASSETS Lida Theodorou, Daniela Massiceti, Luisa M. Zintgraf, Simone Stumpf, Cecily Morrison, Edward Cutrell, Matthew Tobias Harris, Katja Hofmann
2021	A*	`conf`	Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. ICML Luisa M. Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021	J	`jnl`	Implicit Communication as Minimum Entropy Coupling. CoRR Samuel Sokota, Christian Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Shimon Whiteson, Jakob N. Foerster
2021	A*	`conf`	ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. ICCV Daniela Massiceti, Luisa M. Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Edward Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
2021	J	`jnl`	ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. CoRR Daniela Massiceti, Luisa M. Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Edward Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
2021	J	`jnl`	On the Practical Consistency of Meta-Reinforcement Learning Algorithms. CoRR Zheng Xiong, Luisa M. Zintgraf, Jacob Beck, Risto Vuorio, Shimon Whiteson
2021	J	`jnl`	Optimizing piano practice with a utility-based scaffold. CoRR Alexandra Moringen, Sören Rüttgers, Luisa M. Zintgraf, Jason Friedman, Helge J. Ritter
2021	J	`jnl`	VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning. J. Mach. Learn. Res. Luisa M. Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson
2020	J	`jnl`	Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. CoRR Luisa M. Zintgraf, Leo Feng, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2020	—	`conf`	Interactive Multi-objective Reinforcement Learning in Multi-armed Bandits with Gaussian Process Utility Models. ECML/PKDD (3) Diederik M. Roijers, Luisa M. Zintgraf, Pieter Libin, Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé
2020	A*	`conf`	VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. ICLR Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
2019	A*	`conf`	Fast Context Adaptation via Meta-Learning. ICML Luisa M. Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson
2019	J	`jnl`	VIABLE: Fast Adaptation via Backpropagating Learned Loss. CoRR Leo Feng, Luisa M. Zintgraf, Bei Peng, Shimon Whiteson
2019	J	`jnl`	VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. CoRR Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
2018	J	`jnl`	CAML: Fast Context Adaptation via Meta-Learning. CoRR Luisa M. Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson
2018	A*	`conf`	Deep Variational Reinforcement Learning for POMDPs. ICML Maximilian Igl, Luisa M. Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson
2018	J	`jnl`	Deep Variational Reinforcement Learning for POMDPs. CoRR Maximilian Igl, Luisa M. Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson
2018	A	`conf`	Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making. AAMAS Luisa M. Zintgraf, Diederik M. Roijers, Sjoerd Linders, Catholijn M. Jonker, Ann Nowé
2018	J	`jnl`	Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making. CoRR Luisa M. Zintgraf, Diederik M. Roijers, Sjoerd Linders, Catholijn M. Jonker, Ann Nowé
2017	—	`conf`	Interactive Thompson Sampling for Multi-objective Multi-armed Bandits. ADT Diederik M. Roijers, Luisa M. Zintgraf, Ann Nowé
2017	J	`jnl`	Interpretation of microbiota-based diagnostics by explaining individual classifier decisions. BMC Bioinform. A. Eck, Luisa M. Zintgraf, E. F. J. de Groot, Tim G. J. de Meij, Taco S. Cohen, P. H. M. Savelkoul, Max Welling, A. E. Budding
2017	—	`conf`	Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. ICLR (Poster) Luisa M. Zintgraf, Taco S. Cohen, Tameem Adel, Max Welling
2017	J	`jnl`	Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. CoRR Luisa M. Zintgraf, Taco S. Cohen, Tameem Adel, Max Welling
2016	J	`jnl`	A New Method to Visualize Deep Neural Networks. CoRR Luisa M. Zintgraf, Taco S. Cohen, Max Welling