Naturally Occurring Equivariance in Neural Networks
This article is part of the Circuits thread, an experimental format collecting invited short articles and critical commentary delving into the inner workings of neural networks. Curve Detectors High-Low Frequency Detectors Convolutional neural networks contain a hidden world of symmetries within themselves. This symmetry is a powerful tool in understanding the features and circuits inside neural n
Understanding RL Vision
In this article, we apply interpretability techniques to a reinforcement learning (RL) model trained to play the video game CoinRun . Using attribution combined with dimensionality reduction as in , we build an interface for exploring the objects detected by the model, and how they influence its value function and policy. We leverage this interface in several ways. Dissecting failure. We perform a
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