jcpeterson / cifar-10h

Related projects ⓘ

Alternatives and complementary repositories for cifar-10h

• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆39Updated 10 months ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• wronnyhuang / gen-viz
  Code for the paper "Understanding Generalization through Visualizations"
  ☆60Updated 3 years ago
• google-research / heldout-influence-estimation
  ☆61Updated 3 years ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆60Updated 3 years ago
• KaosEngineer / PriorNetworks
  ☆65Updated 4 years ago
• MadryLab / backgrounds_challenge
  ☆138Updated 4 years ago
• ashafaei / OD-test
  OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
  ☆62Updated last year
• shift-happens-benchmark / icml-2022
  Crowdsourcing metrics and test datasets beyond ImageNet (ICML 2022 workshop)
  ☆37Updated 6 months ago
• bethgelab / AnalysisBySynthesis
  Adversarially Robust Neural Network on MNIST.
  ☆64Updated 2 years ago
• rgeirhos / shortcut-perspective
  Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)
  ☆94Updated 2 years ago
• AlexMeinke / certified-certain-uncertainty
  A way to achieve uniform confidence far away from the training data.
  ☆36Updated 3 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆33Updated 3 years ago
• tonylins / simclr-converter
  A PyTorch converter for SimCLR checkpoints
  ☆106Updated 3 years ago
• bneyshabur / generalization-bounds
  Computing various measures and generalization bounds on convolutional and fully connected networks
  ☆35Updated 5 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆85Updated 4 years ago
• chihkuanyeh / concept_exp
  code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"
  ☆51Updated 2 years ago
• BioroboticsLab / IBA
  Information Bottlenecks for Attribution
  ☆75Updated 2 years ago
• jfc43 / robust-ood-detection
  Robust Out-of-distribution Detection in Neural Networks
  ☆72Updated 2 years ago
• P2333 / Max-Mahalanobis-Training
  Max Mahalanobis Training (ICML 2018 + ICLR 2020)
  ☆89Updated 3 years ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆68Updated 6 months ago
• torrvision / focal_calibration
  Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
  ☆155Updated 10 months ago
• PolinaKirichenko / deep_feature_reweighting
  ☆105Updated last year
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆137Updated 4 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆99Updated 2 years ago
• RAIVNLab / supsup
  Code for "Supermasks in Superposition"
  ☆117Updated last year
• tjoo512 / belief-matching-framework
  Belief matching framework official implementation
  ☆38Updated last year
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 3 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆40Updated last year