Alternatives and similar repositories for ood-detection:

Users that are interested in ood-detection are comparing it to the libraries listed below

• MLforHealth / MIMIC_Generalisation
  Code to study the generalisability of benchmark models on non-stationary EHRs.
  ☆14Updated 5 years ago
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆40Updated 2 years ago
• sfme / RVAE_MixedTypes
  Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)
  ☆50Updated 5 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• HazyResearch / model-patching
  Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
  ☆42Updated 4 years ago
• jcyang34 / lspin
  ☆11Updated 2 years ago
• ZidiXiu / ECRT
  Supercharging Imbalanced Data Learning WithCausal Representation Transfer
  ☆12Updated 3 years ago
• kundajelab / labelshiftexperiments
  Label shift experiments
  ☆16Updated 4 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• zackchase / label_shift
  A simple algorithm to identify and correct for label shift.
  ☆21Updated 7 years ago
• imd-iclr / imd
  The Shape of Data: Intrinsic Distance for Comparing Data Distributions
  ☆12Updated 5 years ago
• HazyResearch / mandoline
  (ICML 2021) Mandoline: Model Evaluation under Distribution Shift
  ☆31Updated 3 years ago
• chihkuanyeh / saliency_evaluation
  Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for…
  ☆25Updated 3 years ago
• MadryLab / ImageNetMultiLabel
  Fine-grained ImageNet annotations
  ☆29Updated 4 years ago
• snap-stanford / crust
  [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels
  ☆33Updated 3 years ago
• salesforce / NeuralBayes
  ☆24Updated 3 years ago
• kiankd / corel2019
  Code for AAAI 2019 Network Interpretability workshop paper
  ☆16Updated 3 years ago
• singlasahil14 / barlow
  Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
  ☆35Updated 2 years ago
• samiraabnar / Reflect
  Official Implementation of "Transferring Inductive Biases Through Knowledge Distillation"
  ☆14Updated 4 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆60Updated 4 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated last year
• dmitrykazhdan / concept-based-xai
  Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
  ☆54Updated 2 years ago
• inspire-group / robustness-via-transport
  ☆12Updated 5 years ago
• peterbhase / interpretable-image
  Code for "Interpretable Image Recognition with Hierarchical Prototypes"
  ☆18Updated 5 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 4 years ago
• senwu / dauphin
  An uncertainty-based random sampling algorithm for data augmentation
  ☆30Updated 4 years ago
• AMLab-Amsterdam / DataAugmentationInterventions
  ☆27Updated 4 years ago
• eelenberg / streak
  Interpreting neural networks via the STREAK algorithm (streaming weak submodular maximization)
  ☆23Updated 7 years ago
• ermongroup / BiasAndGeneralization
  ☆26Updated 5 years ago
• minnesotanlp / select-llm
  Parkar and Kim et al.'s paper on Can LLMs Select Important Instructions to Annotate?"
  ☆12Updated 9 months ago