Alternatives and similar repositories for LCODEC-deep-unlearning

Users that are interested in LCODEC-deep-unlearning are comparing it to the libraries listed below

• conditionWang / NTL
  This is the code of ICLR 2022 Oral paper 'Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Au…
  ☆30Updated 2 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• mo666666 / When-Adversarial-Training-Meets-Vision-Transformers
  Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…
  ☆34Updated last year
• kai-wen-yang / CD-VAE
  [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"
  ☆46Updated 3 years ago
• Muzammal-Naseer / ATViT
  Official repository for "On Improving Adversarial Transferability of Vision Transformers" (ICLR 2022--Spotlight)
  ☆72Updated 2 years ago
• OPTML-Group / Unlearn-Sparse
  [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…
  ☆81Updated last year
• snu-mllab / Efficient-Dataset-Condensation
  Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)
  ☆113Updated 2 years ago
• justincui03 / dc_benchmark
  ☆87Updated 2 years ago
• zibojia / RSLAD
  This is the official code for "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"
  ☆45Updated 4 years ago
• chenweixin107 / TrojDiff
  ☆58Updated 2 years ago
• inspire-group / tta_risk
  ☆14Updated 2 years ago
• sdh0818 / FreD
  Official PyTorch implementation for Frequency Domain-based Dataset Distillation [NeurIPS 2023]
  ☆30Updated last year
• alinlab / consistency-adversarial
  Consistency Regularization for Adversarial Robustness (AAAI 2022)
  ☆53Updated 3 years ago
• wzekai99 / DM-Improves-AT
  Code for the paper "Better Diffusion Models Further Improve Adversarial Training" (ICML 2023)
  ☆144Updated 2 years ago
• ziquanliu / CVPR2023-TWINS
  Official code for "TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization", CVPR 2023
  ☆13Updated 2 years ago
• kaiwenzha / contrastive-poisoning
  [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
  ☆31Updated last year
• Muzammal-Naseer / TTP
  Official repository for "On Generating Transferable Targeted Perturbations" (ICCV 2021)
  ☆62Updated 2 years ago
• vinusankars / Convolution-based-Unlearnability
  ☆18Updated 2 years ago
• SonyResearch / IDEAL
  Query-Efficient Data-Free Learning from Black-Box Models
  ☆22Updated 2 years ago
• tmllab / 2023_NeurIPS_AAER
  ☆12Updated 8 months ago
• zwang84 / zsdb3kd
  Knowledge distillation (KD) from a decision-based black-box (DB3) teacher without training data.
  ☆22Updated 3 years ago
• HanxunH / CognitiveDistillation
  [ICLR2023] Distilling Cognitive Backdoor Patterns within an Image
  ☆36Updated last month
• RulinShao / on-the-adversarial-robustness-of-visual-transformer
  Code for the paper "On the Adversarial Robustness of Visual Transformers"
  ☆59Updated 3 years ago
• AISafety-HKUST / Backdoor_Safety_Tuning
  Backdoor Safety Tuning (NeurIPS 2023 & 2024 Spotlight)
  ☆26Updated 11 months ago
• PKU-ML / DYNACL
  [ICLR 2023] Official repository of the paper "Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning"
  ☆18Updated 2 years ago
• point0bar1 / ebm-defense
  PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM
  ☆25Updated 5 years ago
• UniSerj / Random-Projection-Filters
  [CVPR 2023] Adversarial Robustness via Random Projection Filters
  ☆14Updated 2 years ago
• xpf / Data-Efficient-Backdoor-Attacks
  Data-Efficient Backdoor Attacks
  ☆18Updated 3 years ago
• if-loops / selective-synaptic-dampening
  [AAAI, ICLR TP] Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening
  ☆55Updated last year
• inspire-group / proxy-distributions
  [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?
  ☆29Updated 3 years ago