Jordi Grau-Moya

According to our database1, Jordi Grau-Moya authored at least 29 papers between 2012 and 2024.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Grandmaster-Level Chess Without Search.
CoRR, 2024

Learning Universal Predictors.
CoRR, 2024

2023
Language Modeling Is Compression.
CoRR, 2023

Self-Predictive Universal AI.
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.
Proceedings of the International Conference on Machine Learning, 2023

Neural Networks and the Chomsky Hierarchy.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Randomized Positional Encodings Boost Length Generalization of Transformers.
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.
Trans. Mach. Learn. Res., 2022

Beyond Bayes-optimality: meta-learning what you know you don't know.
CoRR, 2022

Neural Networks and the Chomsky Hierarchy.
CoRR, 2022

2021
Model-Free Risk-Sensitive Reinforcement Learning.
CoRR, 2021

Shaking the foundations: delusions in sequence models for interaction and control.
CoRR, 2021

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

Causal Analysis of Agent Behavior for AI Safety.
CoRR, 2021

2019
Disentangled Skill Embeddings for Reinforcement Learning.
CoRR, 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
Non-Equilibrium Relations for Bounded Rational Decision-Making in Changing Environments.
Entropy, 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 under Bounded Rationality and Model Uncertainty: an Information-Theoretic Approach
PhD thesis, 2017

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

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

Adaptive information-theoretic bounded rational decision-making with parametric priors.
CoRR, 2015

2013
Bounded Rational Decision-Making in Changing Environments.
CoRR, 2013

2012
Risk-Sensitivity in Bayesian Sensorimotor Integration.
PLoS Comput. Biol., 2012

Noise-induced up/Down Dynamics in Scale-Free neuronal Networks.
Int. J. Bifurc. Chaos, 2012

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


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