Alternatives and similar repositories for inputgradients

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

• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆39Updated last year
• izmailovpavel / spurious_feature_learning
  ☆45Updated 2 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆71Updated 11 months ago
• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆31Updated 4 years ago
• nitarshan / robust-generalization-measures
  Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)
  ☆28Updated 4 years ago
• uiuctml / fair-classification
  Post-processing for fair classification
  ☆13Updated 3 weeks ago
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 2 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆34Updated 3 years ago
• pdejorge / N-FGSM
  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
• singlasahil14 / salient_imagenet
  Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?
  ☆40Updated 2 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 2 years ago
• huaxiuyao / LISA
  LISA for ICML 2022
  ☆49Updated 2 years ago
• zleizzo / datadeletion
  ☆14Updated 5 years ago
• LTS4 / hold-me-tight
  Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"
  ☆22Updated 3 years ago
• yaodongyu / BiasVariance-AdversarialTraining
  ☆8Updated 4 years ago
• gortizji / linearized-networks
  Source code of "What can linearized neural networks actually say about generalization?
  ☆20Updated 3 years ago
• singlasahil14 / barlow
  Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
  ☆36Updated 2 years ago
• ryoungj / optdom
  [ICLR'22] Self-supervised learning optimally robust representations for domain shift.
  ☆23Updated 3 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆107Updated last year
• MadryLab / failure-directions
  Distilling Model Failures as Directions in Latent Space
  ☆46Updated 2 years ago
• deeplearning-wisc / Spurious_OOD
  ☆23Updated 2 years ago
• yjhuangcd / local-lipschitz
  Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).
  ☆23Updated 2 years ago
• yaodongyu / ProjNorm
  Predicting Out-of-Distribution Error with the Projection Norm
  ☆17Updated 2 years ago
• JonasGeiping / fullbatchtraining
  Training vision models with full-batch gradient descent and regularization
  ☆37Updated 2 years ago
• mpagli / Agree-to-Disagree
  Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"
  ☆36Updated 2 years ago
• google-research / understanding-curricula
  ☆34Updated 3 weeks ago