Alternatives and similar repositories for abstention

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

• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 4 years ago
• BlackHC / batchbald_redux
  Reusable BatchBALD implementation
  ☆79Updated last year
• HazyResearch / hidden-stratification
  Combating hidden stratification with GEORGE
  ☆64Updated 4 years ago
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆124Updated 4 years ago
• HazyResearch / model-patching
  Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
  ☆42Updated 4 years ago
• laura-rieger / deep-explanation-penalization
  Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…
  ☆128Updated 4 years ago
• torrvision / focal_calibration
  Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
  ☆160Updated last year
• google / TrustScore
  To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…
  ☆177Updated 2 years ago
• Jianbo-Lab / L2X
  ☆124Updated 4 years ago
• kundajelab / labelshiftexperiments
  Label shift experiments
  ☆17Updated 4 years ago
• p-lambda / verified_calibration
  Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…
  ☆150Updated 2 years ago
• MLforHealth / MIMIC_Generalisation
  Code to study the generalisability of benchmark models on non-stationary EHRs.
  ☆14Updated 6 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• rgeirhos / shortcut-perspective
  Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)
  ☆99Updated 3 years ago
• FelixAbrahamsson / mixmatch-pytorch
  An implementation of MixMatch with PyTorch
  ☆36Updated 4 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 3 months ago
• suinleelab / path_explain
  A repository for explaining feature attributions and feature interactions in deep neural networks.
  ☆188Updated 3 years ago
• dtak / rrr
  Code/figures in Right for the Right Reasons
  ☆55Updated 4 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 5 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• capybaralet / REx_code_release
  ☆63Updated 4 years ago
• BeenKim / MMD-critic
  ☆134Updated 6 years ago
• zackchase / label_shift
  A simple algorithm to identify and correct for label shift.
  ☆22Updated 7 years ago
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆95Updated 2 years ago
• ashafaei / OD-test
  OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
  ☆62Updated last year
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 5 years ago
• vinayprabhu / Disentanglement_NEURIPS_2019
  On disentangling the menagerie of disentanglement papers
  ☆27Updated 5 years ago
• senwu / dauphin
  An uncertainty-based random sampling algorithm for data augmentation
  ☆30Updated 4 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year