There are 6 repositories under lottery-ticket-hypothesis topic.
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.
A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...
[NeurIPS 2020] "The Lottery Ticket Hypothesis for Pre-trained BERT Networks", Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin
Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH
[NeurIPS'21] "Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly", Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang
[CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang
[ICML 2021] "A Unified Lottery Tickets Hypothesis for Graph Neural Networks", Tianlong Chen*, Yongduo Sui*, Xuxi Chen, Aston Zhang, Zhangyang Wang
This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers"
[ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun Wang*, Santosh Balachandra*, Haoyu Ma*, Zehao Wang, Zhangyang Wang
Implementing "The Lottery Ticket Hypothesis" paper by "Jonathan Frankle, Michael Carbin"
[ICLR 2022] "Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable", by Shaojin Ding, Tianlong Chen, Zhangyang Wang
[ICML 2022] "Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets" by Tianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, Zhangyang Wang.
[ICLR 2021] "GANs Can Play Lottery Too" by Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen
[CVPR 2022] "Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free" by Tianlong Chen*, Zhenyu Zhang*, Yihua Zhang*, Shiyu Chang, Sijia Liu, and Zhangyang Wang
[ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chang, Zhangyang Wang
[ECCV 2022] SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization (ACL 2021)
[NeurIPS 2021] "Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks" by Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David Cox, Yingyan Lin
Code repo for paper: ICML 2020 paper Natural lottery ticket winner: RL for ordinary neural circuits
[TMLR] "Can You Win Everything with Lottery Ticket?" by Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang
This repository contains a Pytorch implementation of the article "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" and an application of this hypothesis to reinforcement learning
Sparsify Your Flux Models
[ICML 2022] "Data-Efficient Double-Win Lottery Tickets from Robust Pre-training" by Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang
[EMNLP 2022] Discovering Language-neutral Sub-networks in Multilingual Language Models.
[NeurIPS'21] "You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership" by Xuxi Chen*, Tianlong Chen*, Zhenyu Zhang, Zhangyang Wang
[arXiv] "Uncovering the Hidden Cost of Model Compression" by Diganta Misra, Agam Goyal, Bharat Runwal, and Pin-Yu Chen
Repository of the course project of CMU 16-824 Visual Learning and Recognition
Compact Image Captioning (CoCA) is an open source image captioning project to promote Green Computer Vision, as well as to make image captioning research accessible to universities, research labs and individual practitioners with limited financial resources.
基于tensorflow lstm模型的彩票预测
Implementation of various neural network pruing methods in pytorch.
A PyTorch implementation of the Lottery Ticket algorithm introduced by Frankle et al. in "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" and enhanced by Zhou et al. in "Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask".
Powerball Lottery Data Probability loader and Parser written in Python