microsoft / fnl_paperLinks
Factorized Neural Layers
☆29Updated 2 years ago
Alternatives and similar repositories for fnl_paper
Users that are interested in fnl_paper are comparing it to the libraries listed below
Sorting:
- ☆23Updated 2 years ago
- Spartan is an algorithm for training sparse neural network models. This repository accompanies the paper "Spartan Differentiable Sparsity…☆24Updated 2 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆52Updated 4 years ago
- Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)☆64Updated 11 months ago
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆31Updated 3 years ago
- ☆14Updated 4 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- An adaptive training algorithm for residual network☆15Updated 4 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
- Latest Weight Averaging (NeurIPS HITY 2022)☆31Updated 2 years ago
- ☆45Updated 4 years ago
- Implementation for ACProp ( Momentum centering and asynchronous update for adaptive gradient methdos, NeurIPS 2021)☆15Updated 3 years ago
- Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi …☆65Updated 4 years ago
- ☆55Updated 11 months 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
- ☆29Updated 2 years ago
- MLPruning, PyTorch, NLP, BERT, Structured Pruning☆20Updated 4 years ago
- ☆12Updated 3 years ago
- ☆70Updated 5 years ago
- A pytorch implementation for the LSTM experiments in the paper: Why Gradient Clipping Accelerates Training: A Theoretical Justification f…☆46Updated 5 years ago
- Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.☆33Updated last year
- ☆45Updated 5 years ago
- Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)☆80Updated last year
- [NeurIPS 2022] DataMUX: Data Multiplexing for Neural Networks☆60Updated 2 years ago
- [ICML 2022] "Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets" by Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wa…☆33Updated 2 years ago
- [ICLR 2023] "Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!" Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen…☆28Updated last year
- ☆18Updated 2 years ago
- [ICML 2021 Oral] "CATE: Computation-aware Neural Architecture Encoding with Transformers" by Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang☆19Updated 4 years ago
- PyTorch implementation of HashedNets☆36Updated 2 years ago
- ☆16Updated 2 years ago