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This is the code used to produce the empyrical results reported in our paper.
This repo presents an official implementation of FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute Classification
Official PyTorch implementation of the paper "SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning"
This repository contains the official PyTorch implementation for the paper:
Open source code for our ECCV2022 accepted paper. https://link.springer.com/chapter/10.1007/978-3-031-20050-2_29
The main features of fanhanwei/bocr are: Filter Pruning.
Projects with overlapping indexed features include: arthurwalraven/cnnslth — This is the code used to produce the empyrical results reported in our paper. bernardo1998/fairgrape — This repo presents an official implementation of FairGRAPE: Fairness-aware GRAdient Pruning mEthod for Face Attribute… boschresearch/sosp — Official PyTorch implementation of the paper "SOSP: Efficiently Capturing Global Correlations by Second-Order… dingxiaoh/resrep — State-of-the-art channel pruning (a.k.a. filter pruning)! This repo contains the code for ResRep: Lossless CNN Pruning… eric-mingjie/network-slimming — Network Slimming (Pytorch) (ICCV 2017). alii-ganjj/interpretationssteeredpruning — This repository contains the official PyTorch implementation for the paper:.