2 citations · 5 across the 4 of their papers we have counts for
3 papers · 1 filter
Learning Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter +8
Meta-learning has emerged as a powerful approach to train neural networks to learn new tasks quickly from limited data. Broad exposure to different tasks leads to versatile represe…
Randomized Positional Encodings Boost Length Generalization of Transformers
Anian Ruoss, Grégoire Delétang, Tim Genewein +5
Transformers have impressive generalization capabilities on tasks with a fixed context length. However, they fail to generalize to sequences of arbitrary length, even for seemingly…
Memory-Based Meta-Learning on Non-Stationary Distributions
Tim Genewein, Grégoire Delétang, Anian Ruoss +7
Memory-based meta-learning is a technique for approximating Bayes-optimal predictors. Under fairly general conditions, minimizing sequential prediction error, measured by the log l…