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Graph Spectral Regularization For Neural Network Interpretability
First, we show a synthetic example that the graph-structured layer can reveal topological features of the data.
Geometry Based Data Generation
We propose a new type of generative model for high-dimensional data that learns a manifold geometry of the data, rather than density, and can generate points evenly along this manifold.
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