Tim Genewein

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 34

Top Topics

Bounded Rationality

Reinforcement Learning

Bregman Divergences

Top Venues

Publications

Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt, John Reid, Tim Genewein
Grandmaster-Level Chess Without Search. CoRR (2024)
Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
Learning Universal Predictors. CoRR (2024)
Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness
Language Modeling Is Compression. ICLR (2024)
Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness
Self-Predictive Universal AI. NeurIPS (2023)
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
Randomized Positional Encodings Boost Length Generalization of Transformers. CoRR (2023)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. CoRR (2023)
Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Chris Cundy, Marcus Hutter, Shane Legg, Joel Veness, Pedro A. Ortega
Neural Networks and the Chomsky Hierarchy. ICLR (2023)
Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness
Language Modeling Is Compression. CoRR (2023)
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness
Randomized Positional Encodings Boost Length Generalization of Transformers. ACL (2) (2023)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. ICML (2023)
Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane X. Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro A. Ortega
Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR (2022)
Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Gregoire Detetang, Markus Kunesch, Shane Legg, Pedro A. Ortega
Your Policy Regularizer is Secretly an Adversary. Trans. Mach. Learn. Res. 2022 (2022)
Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega
Your Policy Regularizer is Secretly an Adversary. CoRR (2022)
Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega
Neural Networks and the Chomsky Hierarchy. CoRR (2022)
Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg
Shaking the foundations: delusions in sequence models for interaction and control. CoRR (2021)
Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega
Model-Free Risk-Sensitive Reinforcement Learning. CoRR (2021)
Grégoire Delétang, Jordi Grau-Moya, Miljan Martic, Tim Genewein, Tom McGrath, Vladimir Mikulik, Markus Kunesch, Shane Legg, Pedro A. Ortega
Causal Analysis of Agent Behavior for AI Safety. CoRR (2021)
Tim Genewein, Tom McGrath, Grégoire Delétang, Vladimir Mikulik, Miljan Martic, Shane Legg, Pedro A. Ortega
Algorithms for Causal Reasoning in Probability Trees. CoRR (2020)
Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega
Meta-trained agents implement Bayes-optimal agents. CoRR (2020)
Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega
Meta-trained agents implement Bayes-optimal agents. NeurIPS (2020)
Chaithanya Kumar Mummadi, Tim Genewein, Dan Zhang, Thomas Brox, Volker Fischer
Norm for Group Gating and Regularization. GCPR (2019)
Giorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen
Sinkhorn AutoEncoders. UAI (2019)
Chaithanya Kumar Mummadi, Tim Genewein, Dan Zhang, Thomas Brox, Volker Fischer
Group Pruning using a Bounded-Lp norm for Group Gating and Regularization. CoRR (2019)
Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg
Meta-learning of Sequential Strategies. CoRR (2019)
Giorgio Patrini, Marcello Carioni, Patrick Forré, Samarth Bhargav, Max Welling, Rianne van den Berg, Tim Genewein, Frank Nielsen
Sinkhorn AutoEncoders. CoRR (2018)
William H. Beluch, Tim Genewein, Andreas Nürnberger, Jan M. Köhler
The Power of Ensembles for Active Learning in Image Classification. CVPR (2018)
Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun
An information-theoretic on-line update principle for perception-action coupling. CoRR (2018)
Jan Achterhold, Jan M. Köhler, Anke Schmeink, Tim Genewein
Variational Network Quantization. ICLR (Poster) (2018)
Jan Hendrik Metzen, Tim Genewein, Volker Fischer, Bastian Bischoff
On Detecting Adversarial Perturbations. ICLR (Poster) (2017)
Jan Hendrik Metzen, Tim Genewein, Volker Fischer, Bastian Bischoff
On Detecting Adversarial Perturbations. CoRR (2017)
Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun
An information-theoretic on-line update principle for perception-action coupling. IROS (2017)
Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun
Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes. CoRR (2016)
Tim Genewein, Daniel A. Braun
Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations. Biol. Cybern. 110 (2-3) (2016)
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)
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 (2015)
Tim Genewein, Eduard Hez, Zeynab Razzaghpanah, Daniel A. Braun
Structure Learning in Bayesian Sensorimotor Integration. PLoS Comput. Biol. 11 (8) (2015)
Tim Genewein, Daniel A. Braun
Abstraction in decision-makers with limited information processing capabilities. CoRR (2013)
Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function. NIPS (2012)
Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function CoRR (2012)