justincosentino / robust-sparse-networksLinks
The Search for Sparse, Robustness Neural Networks
☆11Updated 2 years ago
Alternatives and similar repositories for robust-sparse-networks
Users that are interested in robust-sparse-networks are comparing it to the libraries listed below
Sorting:
- [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“☆24Updated 3 years ago
- Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (ht…☆91Updated 2 years ago
- Adversarial Defense for Ensemble Models (ICML 2019)☆61Updated 5 years ago
- Codebase for the paper "A Gradient Flow Framework for Analyzing Network Pruning"☆20Updated 4 years ago
- [ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun…☆40Updated 3 years ago
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆105Updated 5 years ago
- [NeurIPS'2019] Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu, “Model Compression with Adversarial Robustness: …☆49Updated 3 years ago
- Source Code for ICML 2019 Paper "Shallow-Deep Networks: Understanding and Mitigating Network Overthinking"☆37Updated last year
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆38Updated 5 years ago
- Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks☆66Updated 6 years ago
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- A Closer Look at Accuracy vs. Robustness☆88Updated 4 years ago
- Experiments from "The Generalization-Stability Tradeoff in Neural Network Pruning": https://arxiv.org/abs/1906.03728.☆14Updated 5 years ago
- [CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks☆124Updated 5 years ago
- ☆21Updated 6 years ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 5 years ago
- MACER: MAximizing CErtified Radius (ICLR 2020)☆30Updated 5 years ago
- pytorch implementation of Parametric Noise Injection for adversarial defense☆45Updated 6 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 3 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 5 years ago
- Accelerating Transfer Learning with Robust Neural Nets☆11Updated 5 years ago
- Code release for "Adversarial Robustness vs Model Compression, or Both?"☆90Updated 4 years ago
- Codes for Understanding Architectures Learnt by Cell-based Neural Architecture Search☆28Updated 5 years ago
- InstaHide: Instance-hiding Schemes for Private Distributed Learning☆50Updated 5 years ago
- ☆23Updated 6 years ago
- Source for paper "Attacking Binarized Neural Networks"☆23Updated 7 years ago
- Code accompanying the NeurIPS 2020 paper: WoodFisher (Singh & Alistarh, 2020)☆53Updated 4 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆50Updated 4 years ago
- [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…☆27Updated 3 years ago