It has long been established that predictive models can be transformed i...
Transformers have impressive generalization capabilities on tasks with a...
Memory-based meta-learning is a technique for approximating Bayes-optima...
Meta-training agents with memory has been shown to culminate in Bayes-op...
Reliable generalization lies at the heart of safe ML and AI. However,
un...
Policy regularization methods such as maximum entropy regularization are...
We extend temporal-difference (TD) learning in order to obtain
risk-sens...
The recent phenomenal success of language models has reinvigorated machi...
As machine learning systems become more powerful they also become
increa...
Probability trees are one of the simplest models of causal generative
pr...
Memory-based meta-learning is a powerful technique to build agents that ...