Felix Leibfried

According to our database1, Felix Leibfried authored at least 18 papers between 2015 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2022
Variational Inference for Model-Free and Model-Based Reinforcement Learning.
CoRR, 2022

2021
GPflux: A Library for Deep Gaussian Processes.
CoRR, 2021

Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow.
CoRR, 2021

2020
A Tutorial on Sparse Gaussian Processes and Variational Inference.
CoRR, 2020

Uncertainty in Neural Networks: Approximately Bayesian Ensembling.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment.
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.
Proceedings of the 7th International Conference on Learning Representations, 2019

Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018
Model-Based Stabilisation of Deep Reinforcement Learning.
CoRR, 2018

Balancing Two-Player Stochastic Games with Soft Q-Learning.
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.
PhD thesis, 2017

An Information-Theoretic Optimality Principle for Deep Reinforcement Learning.
CoRR, 2017

An information-theoretic on-line update principle for perception-action coupling.
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.
CoRR, 2016

Bounded Rational Decision-Making in Feedforward Neural Networks.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

2015
A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.
Neural Comput., 2015

Bounded Rationality, Abstraction, and Hierarchical Decision-Making: An Information-Theoretic Optimality Principle.
Frontiers Robotics AI, 2015


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