Tim Genewein

According to our database, Tim Genewein authored at least 29 papers between 2012 and 2024.

Collaborative distances:

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

2024

Grandmaster-Level Chess Without Search.

Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt, John Reid, Tim Genewein

CoRR, 2024

Learning Universal Predictors.

Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness

CoRR, 2024

2023

Language Modeling Is Compression.

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

CoRR, 2023

Self-Predictive Universal AI.

Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Memory-Based Meta-Learning on Non-Stationary Distributions.

Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness

Proceedings of the International Conference on Machine Learning, 2023

Neural Networks and the Chomsky Hierarchy.

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Randomized Positional Encodings Boost Length Generalization of Transformers.

Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

Your Policy Regularizer is Secretly an Adversary.

Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega

Trans. Mach. Learn. Res., 2022

Beyond Bayes-optimality: meta-learning what you know you don't know.

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

CoRR, 2022

Neural Networks and the Chomsky Hierarchy.

Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega

CoRR, 2022

2021

Model-Free Risk-Sensitive Reinforcement Learning.

Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega

CoRR, 2021

Shaking the foundations: delusions in sequence models for interaction and control.

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

CoRR, 2021

Causal Analysis of Agent Behavior for AI Safety.

Grégoire Delétang, Jordi Grau-Moya, Miljan Martic, Tim Genewein, Tom McGrath, Vladimir Mikulik, Markus Kunesch, Shane Legg, Pedro A. Ortega

CoRR, 2021

2020

Algorithms for Causal Reasoning in Probability Trees.

Tim Genewein, Tom McGrath, Grégoire Delétang, Vladimir Mikulik, Miljan Martic, Shane Legg, Pedro A. Ortega

CoRR, 2020

Meta-trained agents implement Bayes-optimal agents.

Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Group Pruning using a Bounded-Lp norm for Group Gating and Regularization.

Chaithanya Kumar Mummadi, Tim Genewein, Dan Zhang, Thomas Brox, Volker Fischer

CoRR, 2019

Meta-learning of Sequential Strategies.

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 M. Botvinick, Shane Legg

CoRR, 2019

Sinkhorn AutoEncoders.

Giorgio Patrini, Rianne van den Berg, Patrick Forré, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Group Pruning Using a Bounded-ℓ_p Norm for Group Gating and Regularization.

Chaithanya Kumar Mummadi, Tim Genewein, Dan Zhang, Thomas Brox, Volker Fischer

Proceedings of the Pattern Recognition, 2019

2018

Variational Network Quantization.

Jan Achterhold, Jan M. Köhler, Anke Schmeink, Tim Genewein

Proceedings of the 6th International Conference on Learning Representations, 2018

The Power of Ensembles for Active Learning in Image Classification.

William H. Beluch, Tim Genewein, Andreas Nürnberger, Jan M. Köhler

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

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

On Detecting Adversarial Perturbations.

Jan Hendrik Metzen, Tim Genewein, Volker Fischer, Bastian Bischoff

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations.

Tim Genewein, Daniel A. Braun

Biol. Cybern., 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

Structure Learning in Bayesian Sensorimotor Integration.

Tim Genewein, Eduard Hez, Zeynab Razzaghpanah, Daniel A. Braun

PLoS Comput. Biol., 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

2013

Abstraction in decision-makers with limited information processing capabilities.

Tim Genewein, Daniel A. Braun

CoRR, 2013

2012

A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function.

Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012