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ORCIDFelix Leibfried
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2020 – today
- 2022
[i13]Felix Leibfried:
Variational Inference for Model-Free and Model-Based Reinforcement Learning. CoRR abs/2209.01693 (2022)- 2021
- [i12]John McLeod, Hrvoje Stojic, Vincent Adam, Dongho Kim, Jordi Grau-Moya, Peter Vrancx, Felix Leibfried:
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow. CoRR abs/2103.14407 (2021) - [i11]Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John:
GPflux: A Library for Deep Gaussian Processes. CoRR abs/2104.05674 (2021) - 2020
- [c8]Tim Pearce, Felix Leibfried, Alexandra Brintrup:
Uncertainty in Neural Networks: Approximately Bayesian Ensembling. AISTATS 2020: 234-244 - [i10]Felix Leibfried, Vincent Dutordoir, S. T. John, Nicolas Durrande:
A Tutorial on Sparse Gaussian Processes and Variational Inference. CoRR abs/2012.13962 (2020)
2010 – 2019
- 2019
- [c7]Felix Leibfried, Jordi Grau-Moya:
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning. CoRL 2019: 360-373 - [c6]Jordi Grau-Moya, Felix Leibfried, Peter Vrancx:
Soft Q-Learning with Mutual-Information Regularization. ICLR (Poster) 2019 - [c5]Felix Leibfried, Sergio Pascual-Diaz, Jordi Grau-Moya:
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment. NeurIPS 2019: 7867-7878 - [i9]Felix Leibfried, Sergio Pascual-Diaz, Jordi Grau-Moya:
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment. CoRR abs/1907.12392 (2019) - [i8]Felix Leibfried, Jordi Grau-Moya:
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning. CoRR abs/1909.05950 (2019) - 2018
- [c4]Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar:
Balancing Two-Player Stochastic Games with Soft Q-Learning. IJCAI 2018: 268-274 - [i7]Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar:
Balancing Two-Player Stochastic Games with Soft Q-Learning. CoRR abs/1802.03216 (2018) - [i6]Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun:
An information-theoretic on-line update principle for perception-action coupling. CoRR abs/1804.05906 (2018) - [i5]Felix Leibfried, Rasul Tutunov, Peter Vrancx, Haitham Bou-Ammar:
Model-Based Stabilisation of Deep Reinforcement Learning. CoRR abs/1809.01906 (2018) - 2017
- [b1]Felix Leibfried:
Decision-making with limited information-processing resources in single-agent and multi-agent systems. University of Tübingen, Germany, 2017, pp. 1-191 - [c3]Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun:
An information-theoretic on-line update principle for perception-action coupling. IROS 2017: 789-796 - [i4]Felix Leibfried, Jordi Grau-Moya, Haitham Bou-Ammar:
An Information-Theoretic Optimality Principle for Deep Reinforcement Learning. CoRR abs/1708.01867 (2017) - 2016
- [c2]Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun:
Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes. ECML/PKDD (2) 2016: 475-491 - [c1]Felix Leibfried, Daniel A. Braun:
Bounded Rational Decision-Making in Feedforward Neural Networks. UAI 2016 - [i3]Felix Leibfried, Daniel Alexander Braun:
Bounded Rational Decision-Making in Feedforward Neural Networks. CoRR abs/1602.08332 (2016) - [i2]Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun:
Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes. CoRR abs/1604.02080 (2016) - [i1]Felix Leibfried, Nate Kushman, Katja Hofmann:
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games. CoRR abs/1611.07078 (2016) - 2015
- [j2]Tim Genewein, Felix Leibfried, Jordi Grau-Moya, Daniel Alexander Braun:
Bounded Rationality, Abstraction, and Hierarchical Decision-Making: An Information-Theoretic Optimality Principle. Frontiers Robotics AI 2: 27 (2015) - [j1]Felix Leibfried, Daniel A. Braun
:
A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker. Neural Comput. 27(8): 1686-1720 (2015)
Coauthor Index
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