Felix Leibfried
Felix Leibfried
Secondmind (formerly PROWLER.io)
Geverifieerd e-mailadres voor prowler.io - Homepage
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Uncertainty in neural networks: Approximately Bayesian ensembling
T Pearce, F Leibfried, A Brintrup, M Zaki, A Neely
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
702020
Bounded rationality, abstraction, and hierarchical decision-making: An information-theoretic optimality principle
T Genewein, F Leibfried, J Grau-Moya, DA Braun
Frontiers in Robotics and AI, 2015
602015
A deep learning approach for joint video frame and reward prediction in Atari games
F Leibfried, N Kushman, K Hofmann
ICML Workshop on Principled Approaches to Deep Learning, 2017
372017
Balancing two-player stochastic games with soft Q-learning
J Grau-Moya, F Leibfried, H Bou-Ammar
International Joint Conference on Artificial Intelligence (IJCAI), 2018
362018
Signaling equilibria in sensorimotor interactions
F Leibfried, J Grau-Moya, DA Braun
Cognition, 2015
332015
Planning with information-processing constraints and model uncertainty in Markov decision processes
J Grau-Moya, F Leibfried, T Genewein, DA Braun
European Conference on Machine Learning (ECML PKDD), 2016
272016
Soft Q-learning with mutual-information regularization
J Grau-Moya, F Leibfried, P Vrancx
International Conference on Learning Representations (ICLR), 2019
252019
An information-theoretic optimality principle for deep reinforcement learning
F Leibfried, J Grau-Moya, H Bou-Ammar
NeurIPS Workshop on Deep Reinforcement Learning, 2018
212018
A reward-maximizing spiking neuron as a bounded rational decision maker
F Leibfried, DA Braun
Neural Computation, 2015
192015
An information-theoretic on-line update principle for perception-action coupling
Z Peng, T Genewein, F Leibfried, DA Braun
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017
132017
Bounded rational decision-making in feedforward neural networks
F Leibfried, DA Braun
Conference on Uncertainty in Artificial Intelligence (UAI), 2016
122016
A unified Bellman optimality principle combining reward maximization and empowerment
F Leibfried, S Pascual-Diaz, J Grau-Moya
Conference on Neural Information Processing Systems (NeurIPS), 2019
112019
Mutual-information regularization in Markov decision processes and actor-critic learning
F Leibfried, J Grau-Moya
Conference on Robot Learning (CoRL), 2019
92019
Model-based regularization for deep reinforcement learning with transcoder networks
F Leibfried, P Vrancx
NeurIPS Workshop on Deep Reinforcement Learning, 2018
32018
Tuneable artificial intelligence
J Grau-Moya, F Leibfried, H Bou-Ammar
US Patent App. 16/759,241, 2020
2020
System architecture for an artificial intelligence platform
A Tukiainen, D Kim, T Nicholson, M Tomczak, JEMDC Flores, N Ferguson, ...
US Patent App. 16/753,580, 2020
2020
A tutorial on sparse Gaussian processes and variational inference
F Leibfried, V Dutordoir, ST John, N Durrande
arXiv preprint arXiv:2012.13962, 2020
2020
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Artikelen 1–17