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David G. T. Barrett

2 accepted papers

2019

Spectral Inference Networks: Unifying Deep and Spectral Learning

ICLR 2019poster

We present Spectral Inference Networks, a framework for learning eigenfunctions of linear operators by stochastic optimization. Spectral Inference Networks generalize Slow Feature Analysis to generic symmetric operators, and are closely related to Variational Monte Carlo methods from computational p…

2017

Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study

ICML 2017poster

Deep neural networks (DNNs) have advanced performance on a wide range of complex tasks, rapidly outpacing our understanding of the nature of their solutions. While past work sought to advance our understanding of these models, none has made use of the rich history of problem descriptions, theories,…

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