ML Anthology

Berkenkamp, Felix

19 publications

TMLR 2025 Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning Under Partial Observability Carlos E. Luis, Alessandro Giacomo Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
ICML 2024 MALIBO: Meta-Learning for Likelihood-Free Bayesian Optimization Jiarong Pan, Stefan Falkner, Felix Berkenkamp, Joaquin Vanschoren
AISTATS 2024 Scalable Meta-Learning with Gaussian Processes Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp
JMLR 2024 Value-Distributional Model-Based Reinforcement Learning Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
MLJ 2023 Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics Felix Berkenkamp, Andreas Krause, Angela P. Schoellig
AISTATS 2023 Model-Based Uncertainty in Value Functions Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters
AISTATS 2022 Transfer Learning with Gaussian Processes for Bayesian Optimization Petru Tighineanu, Kathrin Skubch, Paul Baireuther, Attila Reiss, Felix Berkenkamp, Julia Vinogradska
NeurIPSW 2022 Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation Melrose Roderick, Felix Berkenkamp, Fatemeh Sheikholeslami, J Zico Kolter
NeurIPS 2022 Information-Theoretic Safe Exploration with Gaussian Processes Alessandro Bottero, Carlos Luis, Julia Vinogradska, Felix Berkenkamp, Jan R Peters
ICLR 2022 On-Policy Model Errors in Reinforcement Learning Lukas Froehlich, Maksym Lefarov, Melanie Zeilinger, Felix Berkenkamp
NeurIPS 2020 Efficient Model-Based Reinforcement Learning Through Optimistic Policy Search and Planning Sebastian Curi, Felix Berkenkamp, Andreas Krause
ICLR 2020 Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning Noah Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin Riedmiller
L4DC 2020 Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models Sebastian Curi, Silvan Melchior, Felix Berkenkamp, Andreas Krause
ICLR 2019 Information-Directed Exploration for Deep Reinforcement Learning Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp, Andreas Krause
JMLR 2019 No-Regret Bayesian Optimization with Unknown Hyperparameters Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
NeurIPS 2019 Safe Exploration for Interactive Machine Learning Matteo Turchetta, Felix Berkenkamp, Andreas Krause
CoRL 2018 The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems Spencer M. Richards, Felix Berkenkamp, Andreas Krause
NeurIPS 2017 Safe Model-Based Reinforcement Learning with Stability Guarantees Felix Berkenkamp, Matteo Turchetta, Angela Schoellig, Andreas Krause
NeurIPS 2016 Safe Exploration in Finite Markov Decision Processes with Gaussian Processes Matteo Turchetta, Felix Berkenkamp, Andreas Krause