Alternatives and similar repositories for 2023_NeurIPS_AAER

Users that are interested in 2023_NeurIPS_AAER are comparing it to the libraries listed below

• ZFancy / IAD
  [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers
  ☆21Updated 3 years ago
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 4 years ago
• kai-wen-yang / CD-VAE
  [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"
  ☆46Updated 3 years ago
• Alexkael / Randomized-Adversarial-Training
  ☆31Updated last year
• dwDavidxd / MIAT
  Improving Adversarial Robustness via Mutual Information Estimation
  ☆11Updated last year
• vsingh-group / LCODEC-deep-unlearning
  Code for CVPR22 paper "Deep Unlearning via Randomized Conditionally Independent Hessians"
  ☆25Updated 3 years ago
• inspire-group / MIAdefenseSELENA
  [USENIX Security 2022] Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture
  ☆17Updated 3 years ago
• inspire-group / tta_risk
  ☆14Updated 2 years ago
• Saehyung-Lee / cifar10_challenge
  Code for the CVPR 2020 article "Adversarial Vertex mixup: Toward Better Adversarially Robust Generalization"
  ☆13Updated 5 years ago
• conditionWang / NTL
  This is the code of ICLR 2022 Oral paper 'Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Au…
  ☆29Updated last year
• zibojia / RSLAD
  This is the official code for "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"
  ☆43Updated 4 years ago
• kaiwenzha / contrastive-poisoning
  [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
  ☆31Updated last year
• lafeat / apbench
  APBench: A Unified Availability Poisoning Attack and Defenses Benchmark (TMLR 08/2024)
  ☆35Updated 5 months ago
• renjie3 / TUE
  Code for Transferable Unlearnable Examples
  ☆21Updated 2 years ago
• zhuohuangai / SharpDRO
  Code for CVPR 2023 Robust Generalization against Photon-Limited Corruptions via Worst-Case Sharpness Minimization
  ☆13Updated 2 years ago
• jiaxiaojunQAQ / FGSM-PGI
  Code for Prior-Guided Adversarial Initialization for Fast Adversarial Training (ECCV2022)
  ☆26Updated 2 years ago
• ChaojianYu / Robust-Weight-Perturbation
  Implementation for <Robust Weight Perturbation for Adversarial Training> in IJCAI'22.
  ☆15Updated 3 years ago
• QizhouWang / MAIL
  source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training
  ☆11Updated 3 years ago
• PKU-ML / CFA
  ☆20Updated 6 months ago
• ChaojianYu / Understanding-Robust-Overfitting
  Implementation for <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.
  ☆12Updated 3 years ago
• IBM / composite-adv
  [CVPR23] "Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations" by Lei Hsi…
  ☆24Updated last week
• HanxunH / CognitiveDistillation
  [ICLR2023] Distilling Cognitive Backdoor Patterns within an Image
  ☆36Updated 2 weeks ago
• dwDavidxd / CAFD
  Removing Adversarial Noise in Class Activation Feature Space
  ☆14Updated last year
• YisenWang / MART
  Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
  ☆151Updated 4 years ago
• jiamingzhang94 / Unlearnable-Clusters
  CVPR2023: Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples
  ☆22Updated 2 years ago
• dwDavidxd / ARN
  Towards Defending against Adversarial Examples via Attack-Invariant Features
  ☆12Updated last year
• bymavis / CAS_ICLR2021
  ☆58Updated 3 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆38Updated 9 months ago
• imrahulr / adversarial_robustness_pytorch
  Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…
  ☆97Updated 3 years ago