MingSun-Tse / Smile-PruningLinks
A generic code base for neural network pruning, especially for pruning at initialization.
☆30Updated 2 years ago
Alternatives and similar repositories for Smile-Pruning
Users that are interested in Smile-Pruning are comparing it to the libraries listed below
Sorting:
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆33Updated 2 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
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated last year
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 3 years ago
- ☆30Updated 3 years ago
- ☆22Updated 5 years ago
- Code for ViTAS_Vision Transformer Architecture Search☆50Updated 3 years ago
- Data-Free Network Quantization With Adversarial Knowledge Distillation PyTorch☆30Updated 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
- [ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun…☆39Updated 3 years ago
- [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective☆37Updated 2 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year
- [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…☆27Updated 2 years ago
- Data-free knowledge distillation using Gaussian noise (NeurIPS paper)☆15Updated 2 years ago
- [ICLR 2022]: Fast AdvProp☆35Updated 3 years ago
- Comparison of method "Pruning at initialization prior to training" (Synflow/SNIP/GraSP) in PyTorch☆16Updated last year
- Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020☆28Updated 3 years ago
- BESA is a differentiable weight pruning technique for large language models.☆17Updated last year
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆53Updated last year
- ☆19Updated 2 years ago
- [ICLR 2022] "Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining" by Lu Miao*, Xiaolong Luo*, T…☆30Updated 3 years ago
- ☆25Updated 3 years ago
- [ICLR'21] Neural Pruning via Growing Regularization (PyTorch)☆83Updated 3 years ago
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆28Updated 2 years ago
- Code for our ICLR'2021 paper "DrNAS: Dirichlet Neural Architecture Search"☆43Updated 4 years ago
- ☆10Updated 4 years ago
- ☆43Updated last year
- In progress.☆64Updated last year
- [ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, S…☆25Updated 3 years ago