Neural Networks Trained to Solve Differential Equations Learn General Representations

NeurIPS 2018 Martin MagillFaisal QureshiHendrick W. de Haan

We introduce a technique based on the singular vector canonical correlation analysis (SVCCA) for measuring the generality of neural network layers across a continuously-parametrized set of tasks. We illustrate this method by studying generality in neural networks trained to solve parametrized boundary value problems based on the Poisson partial differential equation... (read more)

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