locuslab / intermediate_robustnessLinks
☆16Updated 3 years ago
Alternatives and similar repositories for intermediate_robustness
Users that are interested in intermediate_robustness are comparing it to the libraries listed below
Sorting:
- Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"☆22Updated 3 years ago
- ☆25Updated 5 years ago
- [ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun…☆39Updated 3 years ago
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 2 years ago
- ☆18Updated 2 years ago
- ☆8Updated 4 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- Implementation for ACProp ( Momentum centering and asynchronous update for adaptive gradient methdos, NeurIPS 2021)☆15Updated 3 years ago
- kyleliang919 / Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferabilitycode for ICML 2021 paper in which we explore the relationship between adversarial transferability and knowledge transferability.☆17Updated 2 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"☆23Updated 6 years ago
- Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]☆20Updated last year
- PRIME: A Few Primitives Can Boost Robustness to Common Corruptions☆42Updated 2 years ago
- [ICML 2022] "Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness" by Tianlong Chen*, Huan Zhang*, Zhenyu Zhang, Shiyu…☆16Updated 2 years ago
- Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression☆18Updated 3 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆36Updated 3 years ago
- ☆20Updated 4 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆19Updated 2 years ago
- Experiments from "The Generalization-Stability Tradeoff in Neural Network Pruning": https://arxiv.org/abs/1906.03728.☆15Updated 4 years ago
- Certified Patch Robustness via Smoothed Vision Transformers☆42Updated 3 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Fine-grained ImageNet annotations☆29Updated 5 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆23Updated 2 years ago
- ☆19Updated 3 years ago
- ☆15Updated 2 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 3 years ago
- SGD with large step sizes learns sparse features [ICML 2023]☆32Updated 2 years ago
- Learning perturbation sets for robust machine learning☆65Updated 3 years ago
- Research prototype of deletion efficient k-means algorithms☆24Updated 5 years ago