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Found 3 papers, 1 papers with code
On Model Explanations with Transferable Neural Pathways
Neural pathways as model explanations consist of a sparse set of neurons that provide the same level of prediction performance as the whole model.
Catch Missing Details: Image Reconstruction with Frequency Augmented Variational Autoencoder
The popular VQ-VAE models reconstruct images through learning a discrete codebook but suffer from a significant issue in the rapid quality degradation of image reconstruction as the compression rate rises.
Gradient Frequency Modulation for Visually Explaining Video Understanding Models
In many applications, it is essential to understand why a machine learning model makes the decisions it does, but this is inhibited by the black-box nature of state-of-the-art neural networks.
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