naver / force
☆14Updated 4 years ago
Alternatives and similar repositories for force:
Users that are interested in force are comparing it to the libraries listed below
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆31Updated 3 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- Lookahead: A Far-sighted Alternative of Magnitude-based Pruning (ICLR 2020)☆33Updated 4 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆103Updated 5 years ago
- Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection☆21Updated 4 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
- Soft Threshold Weight Reparameterization for Learnable Sparsity☆89Updated 2 years ago
- Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.☆56Updated 3 years ago
- [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
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated last year
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆49Updated 4 years ago
- Codebase for the paper "A Gradient Flow Framework for Analyzing Network Pruning"☆21Updated 4 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Code base for SRSGD.☆28Updated 5 years ago
- [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“☆24Updated 3 years ago
- ☆58Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint☆31Updated 3 years ago
- [ICML 2021] "Efficient Lottery Ticket Finding: Less Data is More" by Zhenyu Zhang*, Xuxi Chen*, Tianlong Chen*, Zhangyang Wang☆25Updated 3 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- Code for the ICML 2021 and ICLR 2022 papers: Skew Orthogonal Convolutions, Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100☆18Updated 3 years ago
- Code for testing DCT plus Sparse (DCTpS) networks☆14Updated 3 years ago
- Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing …☆52Updated 3 years ago
- This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?☆12Updated last year
- [ICLR 2022] "Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining" by Lu Miao*, Xiaolong Luo*, T…☆29Updated 3 years ago
- [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
- Comparison of method "Pruning at initialization prior to training" (Synflow/SNIP/GraSP) in PyTorch☆16Updated 11 months ago
- ☆45Updated 5 years ago
- Encodings for neural architecture search☆29Updated 4 years ago