Hofmann, Katja

36 publications

ICML 2025 Scaling Laws for Pre-Training Agents and World Models Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann

ICLRW 2025 Scaling Laws for Pre-Training Agents and World Models Tim Pearce, Tabish Rashid, David Bignell, Raluca Georgescu, Sam Devlin, Katja Hofmann

AISTATS 2024 Learning Safety Constraints from Demonstrations with Unknown Rewards David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

ICMLW 2024 Transformer Neural Autoregressive Flows Massimiliano Patacchiola, Aliaksandra Shysheya, Katja Hofmann, Richard E. Turner

CoLLAs 2023 Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation Massimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E. Turner

ICLR 2023 Imitating Human Behaviour with Diffusion Models Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin

NeurIPSW 2022 Contextual Squeeze-and-Excitation Massimiliano Patacchiola, John F Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E Turner

NeurIPS 2022 Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard Turner

AAAI 2022 Deterministic and Discriminative Imitation (d2-Imitation): Revisiting Adversarial Imitation for Sample Efficiency Mingfei Sun, Sam Devlin, Katja Hofmann, Shimon Whiteson

NeurIPSW 2022 Imitating Human Behaviour with Diffusion Models Tim Pearce, Tabish Rashid, Anssi Kanervisto, David Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, Sam Devlin

ICML 2022 Interactively Learning Preference Constraints in Linear Bandits David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

ICLRW 2022 Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin

NeurIPS 2022 Uni[MASK]: Unified Inference in Sequential Decision Problems Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew Hausknecht, Anca Dragan, Sam Devlin

ICML 2021 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning Luisa M Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson

NeurIPS 2021 Grounding Spatio-Temporal Language with Transformers Tristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer

NeurIPS 2021 Memory Efficient Meta-Learning with Large Images John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard Turner

ICML 2021 Navigation Turing Test (NTT): Learning to Evaluate Human-like Navigation Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann

ICCV 2021 ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition Daniela Massiceti, Luisa Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Edward Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf

UAI 2021 Strategically Efficient Exploration in Competitive Multi-Agent Reinforcement Learning Robert Loftin, Aadirupa Saha, Sam Devlin, Katja Hofmann

ICML 2021 TeachMyAgent: A Benchmark for Automatic Curriculum Learning in Deep RL Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer

JMLR 2021 VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning Luisa Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson

ICLR 2020 AMRL: Aggregated Memory for Reinforcement Learning Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann

IJCAI 2020 Automatic Curriculum Learning for Deep RL: A Short Survey Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer

ICLR 2020 Conservative Uncertainty Estimation by Fitting Prior Networks Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner

ICLR 2020 VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning Luisa Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson

AISTATS 2020 Variational Integrator Networks for Physically Structured Embeddings Steindor Saemundsson, Alexander Terenin, Katja Hofmann, Marc Deisenroth

NeurIPS 2019 Better Exploration with Optimistic Actor Critic Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann

ICML 2019 Fast Context Adaptation via Meta-Learning Luisa Zintgraf, Kyriacos Shiarli, Vitaly Kurin, Katja Hofmann, Shimon Whiteson

NeurIPS 2019 Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann

NeurIPS 2019 Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning David Janz, Jiri Hron, Przemysław Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Sebastian Tschiatschek

CoRL 2019 Teacher Algorithms for Curriculum Learning of Deep RL in Continuously Parameterized Environments Rémy Portelas, Cédric Colas, Katja Hofmann, Pierre-Yves Oudeyer

IJCAI 2018 Advancements in Dueling Bandits Yanan Sui, Masrour Zoghi, Katja Hofmann, Yisong Yue

UAI 2018 Meta Reinforcement Learning with Latent Variable Gaussian Processes Steindór Sæmundsson, Katja Hofmann, Marc Peter Deisenroth

AAAI 2016 Collective Noise Contrastive Estimation for Policy Transfer Learning Weinan Zhang, Ulrich Paquet, Katja Hofmann

IJCAI 2016 The Malmo Platform for Artificial Intelligence Experimentation Matthew Johnson, Katja Hofmann, Tim Hutton, David Bignell

COLT 2015 Contextual Dueling Bandits Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi