SHI-Labs / DiSparse-Multitask-Model-CompressionLinks
[CVPR 2022] DiSparse: Disentangled Sparsification for Multitask Model Compression
☆13Updated 2 years ago
Alternatives and similar repositories for DiSparse-Multitask-Model-Compression
Users that are interested in DiSparse-Multitask-Model-Compression are comparing it to the libraries listed below
Sorting:
- [NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang…☆90Updated last year
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- NAS Benchmark in "Prioritized Architecture Sampling with Monto-Carlo Tree Search", CVPR2021☆37Updated 3 years ago
- (CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers☆25Updated 3 months ago
- Revisiting Parameter Sharing for Automatic Neural Channel Number Search, NeurIPS 2020☆21Updated 4 years ago
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆40Updated 2 years ago
- ☆57Updated 3 years ago
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆32Updated 2 years ago
- ☆17Updated 2 years ago
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆25Updated 3 years ago
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆52Updated last year
- [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective☆37Updated 2 years ago
- ☆22Updated 5 years ago
- Code for ViTAS_Vision Transformer Architecture Search☆50Updated 3 years ago
- Towards Compact CNNs via Collaborative Compression☆11Updated 3 years ago
- ☆25Updated 3 years ago
- [ICML 2021 Oral] "CATE: Computation-aware Neural Architecture Encoding with Transformers" by Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang☆19Updated 3 years ago
- ☆17Updated 3 years ago
- ☆10Updated 4 years ago
- [ICLR 2022] "As-ViT: Auto-scaling Vision Transformers without Training" by Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wa…☆76Updated 3 years ago
- Codes for paper "Few Shot Network Compression via Cross Distillation", AAAI 2020.☆31Updated 5 years ago
- ☆31Updated 4 years ago
- A pytorch implementation of the ICCV2021 workshop paper SimDis: Simple Distillation Baselines for Improving Small Self-supervised Models☆14Updated 3 years ago
- [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…☆73Updated 2 years ago
- This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".☆43Updated 3 years ago
- Pytorch implementation of our paper accepted by TPAMI 2023 — Lottery Jackpots Exist in Pre-trained Models☆34Updated last year
- ☆21Updated 2 years ago
- ☆13Updated 11 months ago
- PyTorch implementation of "Deep Transferring Quantization" (ECCV2020)☆18Updated 2 years ago
- Data-Free Neural Architecture Search via Recursive Label Calibration. ECCV 2022.☆32Updated 2 years ago