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Neil C. Rabinowitz

3 accepted papers

2022

Tell me why! Explanations support learning relational and causal structure

ICML 2022spotlight

Inferring the abstract relational and causal structure of the world is a major challenge for reinforcement-learning (RL) agents. For humans, language{—}particularly in the form of explanations{—}plays a considerable role in overcoming this challenge. Here, we show that language can play a similar ro…

2019

Relational Forward Models for Multi-Agent Learning

ICLR 2019poster

The behavioral dynamics of multi-agent systems have a rich and orderly structure, which can be leveraged to understand these systems, and to improve how artificial agents learn to operate in them. Here we introduce Relational Forward Models (RFM) for multi-agent learning, networks that can learn to…

Cited by 95SourcePDFScholar
2018

On the importance of single directions for generalization

ICLR 2018poster

Despite their ability to memorize large datasets, deep neural networks often achieve good generalization performance. However, the differences between the learned solutions of networks which generalize and those which do not remain unclear. Additionally, the tuning properties of single directions (d…

Cited by 388SourcePDFScholar