[ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers
☆22Feb 20, 2022Updated 4 years ago
Alternatives and similar repositories for IAD
Users that are interested in IAD are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- This is the official code for "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"☆45Aug 29, 2021Updated 4 years ago
- the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral☆59Apr 13, 2021Updated 5 years ago
- Code for the paper Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation (CVPR 2023).☆34May 26, 2023Updated 3 years ago
- [NeurIPS 2022] "Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks"☆13Nov 11, 2022Updated 3 years ago
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆38Nov 27, 2023Updated 2 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Codes for ICCV 2021 paper "AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Met…☆12Mar 3, 2022Updated 4 years ago
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Mar 15, 2022Updated 4 years ago
- [ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"☆31Dec 28, 2025Updated 6 months ago
- [NeurIPS 2023 Spotlight] Combating Representation Learning Disparity with Geometric Harmonization☆24May 14, 2025Updated last year
- Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)☆126Sep 13, 2023Updated 2 years ago
- Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…☆98Mar 4, 2022Updated 4 years ago
- Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective☆19Jun 7, 2024Updated 2 years ago
- [ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"☆18Jul 7, 2023Updated 2 years ago
- [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training☆32Jan 9, 2022Updated 4 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- ☆12May 6, 2022Updated 4 years ago
- ☆21Jun 6, 2024Updated 2 years ago
- ICLR 2023 paper "Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness" by Yuancheng Xu, Yanchao Sun, Micah Gold…☆26May 2, 2023Updated 3 years ago
- Code for the paper "Better Diffusion Models Further Improve Adversarial Training" (ICML 2023)☆144Jul 31, 2023Updated 2 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆49Dec 30, 2021Updated 4 years ago
- [NeurIPS 2023]Federated Learning with Bilateral Curation for Partially Class-Disjoint Data☆14Aug 1, 2025Updated 10 months ago
- video_attack; Efficient Sparse Attacks on Videos using Reinforcement Learning☆15Oct 25, 2021Updated 4 years ago
- Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"☆746May 16, 2024Updated 2 years ago
- TRADES (TRadeoff-inspired Adversarial DEfense via Surrogate-loss minimization)☆555Mar 30, 2023Updated 3 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- [ICLR 2026] "Co-rewarding: Stable Self-supervised RL for Eliciting Reasoning in Large Language Models"☆58Feb 4, 2026Updated 4 months ago
- [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…☆29Dec 30, 2021Updated 4 years ago
- Not All Poisons are Created Equal: Robust Training against Data Poisoning (ICML 2022)