Alternatives and similar repositories for datadeletion:

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

• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 2 years ago
• amiratag / neuronshapley
  Code for "Neuron Shapley: Discovering the Responsible Neurons"
  ☆23Updated 8 months ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• fra31 / robust-finetuning
  Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"
  ☆18Updated 2 years ago
• eth-sri / smoothing-ensembles
  [ICLR 2022] Boosting Randomized Smoothing with Variance Reduced Classifiers
  ☆12Updated 2 years ago
• yangarbiter / rare-spurious-correlation
  Understanding Rare Spurious Correlations in Neural Network
  ☆12Updated 2 years ago
• JialinMao / private_CNN
  ☆10Updated 2 years ago
• uiuctml / fair-classification
  Post-processing for fair classification
  ☆12Updated 2 months ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 3 years ago
• yjhuangcd / local-lipschitz
  Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).
  ☆22Updated 2 years ago
• liuchen11 / AdversaryLossLandscape
  On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]
  ☆35Updated 3 years ago
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 2 years ago
• OPTML-Group / Unlearn-WorstCase
  [ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, …
  ☆19Updated 3 months ago
• mueller-mp / SAM-ON
  ☆34Updated 11 months ago
• HazyResearch / correct-n-contrast
  Official code repository for Correct-N-Contrast
  ☆20Updated 2 years ago
• pratyushmaini / localizing-memorization
  Official Repository for ICML 2023 paper "Can Neural Network Memorization Be Localized?"
  ☆17Updated last year
• BorealisAI / mma_training
  Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"
  ☆34Updated 4 years ago
• kaiwenzha / contrastive-poisoning
  [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
  ☆29Updated last year
• nvedant07 / Fairness-Through-Robustness
  Official code for FAccT'21 paper "Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning" https://arxiv.org/abs…
  ☆12Updated 3 years ago
• uiuctml / ISR
  Invariant-feature Subspace Recovery (ISR)
  ☆23Updated 2 years ago
• ryokamoi / pytorch_influence_functions
  This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence…
  ☆16Updated 4 years ago
• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆55Updated 2 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 4 years ago
• litian96 / AdaDPS
  Private Adaptive Optimization with Side Information (ICML '22)
  ☆16Updated 2 years ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆68Updated 8 months ago
• k-hanawa / criteria_for_instance_based_explanation
  ☆9Updated last year
• facebookresearch / certified-removal
  Certified Removal from Machine Learning Models
  ☆63Updated 3 years ago
• kohpangwei / group-influence-release
  ☆50Updated last year
• locuslab / robust_union
  [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
  ☆26Updated 5 months ago