Felix Leibfried

According to our database, Felix Leibfried authored at least 18 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Variational Inference for Model-Free and Model-Based Reinforcement Learning.

Felix Leibfried

CoRR, 2022

2021

GPflux: A Library for Deep Gaussian Processes.

Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John

CoRR, 2021

Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow.

John McLeod, Hrvoje Stojic, Vincent Adam, Dongho Kim, Jordi Grau-Moya, Peter Vrancx, Felix Leibfried

CoRR, 2021

2020

A Tutorial on Sparse Gaussian Processes and Variational Inference.

Felix Leibfried, Vincent Dutordoir, S. T. John, Nicolas Durrande

CoRR, 2020

Uncertainty in Neural Networks: Approximately Bayesian Ensembling.

Tim Pearce, Felix Leibfried, Alexandra Brintrup

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment.

Felix Leibfried, Sergio Pascual-Diaz, Jordi Grau-Moya

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Soft Q-Learning with Mutual-Information Regularization.

Jordi Grau-Moya, Felix Leibfried, Peter Vrancx

Proceedings of the 7th International Conference on Learning Representations, 2019

Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning.

Felix Leibfried, Jordi Grau-Moya

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

Model-Based Stabilisation of Deep Reinforcement Learning.

Felix Leibfried, Rasul Tutunov, Peter Vrancx, Haitham Bou-Ammar

CoRR, 2018

Balancing Two-Player Stochastic Games with Soft Q-Learning.

Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Decision-making with limited information-processing resources in single-agent and multi-agent systems.

Felix Leibfried

PhD thesis, 2017

An Information-Theoretic Optimality Principle for Deep Reinforcement Learning.

Felix Leibfried, Jordi Grau-Moya, Haitham Bou-Ammar

CoRR, 2017

An information-theoretic on-line update principle for perception-action coupling.

Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

2016

A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games.

Felix Leibfried, Nate Kushman, Katja Hofmann

CoRR, 2016

Bounded Rational Decision-Making in Feedforward Neural Networks.

Felix Leibfried, Daniel A. Braun

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes.

Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

2015

A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.

Felix Leibfried, Daniel A. Braun

Neural Comput., 2015

Bounded Rationality, Abstraction, and Hierarchical Decision-Making: An Information-Theoretic Optimality Principle.

Tim Genewein, Felix Leibfried, Jordi Grau-Moya, Daniel Alexander Braun

Frontiers Robotics AI, 2015