[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs
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Updated
Aug 24, 2024 - Python
[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs
Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)
Collection of recent methods on (deep) neural network compression and acceleration.
A simple and effective LLM pruning approach.
This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.
[TPAMI 2023, NeurIPS 2020] Code release for "Deep Multimodal Fusion by Channel Exchanging"
Code for "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019), "SCOP: Scientific Control for Reliable Neural Network Pruning" (NeurIPS 2020) and “Manifold Regularized Dynamic Network Pruning” (CVPR 2021).
(CVPR 2021, Oral) Dynamic Slimmable Network
[ICLR 2020]: 'AtomNAS: Fine-Grained End-to-End Neural Architecture Search'
Efficient Sparse-Winograd Convolutional Neural Networks (ICLR 2018)
[NeurIPS 2023] Structural Pruning for Diffusion Models
PAGCP for the compression of YOLOv5
Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934
SNIP: SINGLE-SHOT NETWORK PRUNING BASED ON CONNECTION SENSITIVITY
[TPAMI 2024] This is the official repository for our paper: ''Pruning Self-attentions into Convolutional Layers in Single Path''.
CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders
[Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning
Lookahead: A Far-sighted Alternative of Magnitude-based Pruning (ICLR 2020)
Tensorflow codes for "Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers"
In this repository using the sparse training, group channel pruning and knowledge distilling for YOLOV4,
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