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Efficient-Deep-Learning
Collection of recent methods on (deep) neural network compression and acceleration.Collaborative-Distillation
[CVPR'20] Collaborative Distillation for Ultra-Resolution Universal Style Transfer (PyTorch)Regularization-Pruning
[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)ASSL
[NeurIPS'21 Spotlight] Aligned Structured Sparsity Learning for Efficient Image Super-Resolution (PyTorch)Awesome-Pruning-at-Initialization
[IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.Smile-Pruning
A generic code base for neural network pruning, especially for pruning at initialization.Why-the-State-of-Pruning-so-Confusing
[Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruningsmilelogging
Python logging package for easy reproducible experimenting in researchTPP
[ICLR'23] Trainability Preserving Neural Pruning (PyTorch)Awesome-Efficient-ViT
Recent Advances on Efficient Vision TransformersSRP
[ICLR'22] PyTorch code for our paper "Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning"Caffe_IncReg
[IJCNN'19, IEEE JSTSP'19] Caffe code for our paper "Structured Pruning for Efficient ConvNets via Incremental Regularization"; [BMVC'18] "Structured Probabilistic Pruning for Convolutional Neural Network Acceleration"WritingTips
"Good scientific writing is not a matter of life and death; it is much more serious than that."Efficient-NeRF
UtilsHub
LowlevelVision
paper collection for low-level visionAdversarialAttacks
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