Alternatives and similar repositories for Breaking_Down_OOD_Detection

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

• j-cb / GOOD
  Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data
  ☆13Updated 3 years ago
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 3 years ago
• AlexMeinke / certified-certain-uncertainty
  A way to achieve uniform confidence far away from the training data.
  ☆38Updated 4 years ago
• AmirooR / IntraOrderPreservingCalibration
  ☆12Updated 3 years ago
• deeplearning-wisc / Spurious_OOD
  ☆23Updated 3 years ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆73Updated last year
• jfc43 / informative-outlier-mining
  We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…
  ☆57Updated 3 years ago
• schzhu / learning-adversarially-robust-representations
  Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2…
  ☆23Updated 5 years ago
• yjhuangcd / local-lipschitz
  Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).
  ☆25Updated 3 years ago
• uiuctml / fair-classification
  Post-processing for fair classification
  ☆16Updated 7 months ago
• RenkunNi / MetaAug
  ☆28Updated 4 years ago
• alinlab / LfF
  Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)
  ☆94Updated 5 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• ae-foster / invclr
  Improving Transformation Invariance in Contrastive Representation Learning
  ☆13Updated 4 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 3 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 3 years ago
• chihhuiho / CLAE
  Implementation of Contrastive Learning with Adversarial Examples
  ☆29Updated 5 years ago
• AKuzina / attack_vae
  Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks
  ☆13Updated 3 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 4 years ago
• fra31 / robust-finetuning
  Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"
  ☆19Updated 3 years ago
• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆30Updated 5 years ago
• arobey1 / mbdg
  ☆36Updated 4 years ago
• Johswald / learning_where_to_learn
  ☆39Updated last year
• izmailovpavel / spurious_feature_learning
  ☆47Updated 3 years ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆89Updated 3 years ago
• uiuctml / ISR
  Invariant-feature Subspace Recovery (ISR)
  ☆23Updated 3 years ago
• VectorInstitute / gram-ood-detection
  ☆46Updated 5 years ago
• ynysjtu / ood_bench
  ☆49Updated 3 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆111Updated 2 years ago
• MadryLab / BREEDS-Benchmarks
  ☆56Updated 5 years ago