Sparsely Reconstructed Graphs (SpaRG) for robust and interpretable fMRI analysis using GNNs and VAEs.
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Updated
Sep 22, 2024 - Python
Sparsely Reconstructed Graphs (SpaRG) for robust and interpretable fMRI analysis using GNNs and VAEs.
Simple Implementation of the CVPR 2024 Paper "JointSQ: Joint Sparsification-Quantization for Distributed Learning"
Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
Code for CRATE (Coding RAte reduction TransformEr).
Sparsity-aware deep learning inference runtime for CPUs
Feather is a module that enables effective sparsification of neural networks during training. This repository accompanies the paper "Feather: An Elegant Solution to Effective DNN Sparsification" (BMVC2023).
The communication efficiency of federated learning is improved by sparsifying the parameters uploaded by the clients.
(Unstructured) Weight Pruning via Adaptive Sparsity Loss
Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.
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