Alternatives and similar repositories for out-of-distribution-detection:

Users that are interested in out-of-distribution-detection are comparing it to the libraries listed below

• alinlab / Confident_classifier
  Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018
  ☆178Updated 4 years ago
• hendrycks / error-detection
  A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
  ☆226Updated 6 years ago
• nazim1021 / OOD-detection-using-OECC
  Outlier Exposure with Confidence Control for Out-of-Distribution Detection
  ☆69Updated 3 years ago
• pokaxpoka / deep_Mahalanobis_detector
  Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".
  ☆343Updated 5 years ago
• hendrycks / ss-ood
  Self-Supervised Learning for OOD Detection (NeurIPS 2019)
  ☆266Updated 3 years ago
• ShiyuLiang / odin-pytorch
  Principled Detection of Out-of-Distribution Examples in Neural Networks
  ☆201Updated 7 years ago
• Newbeeer / L_DMI
  Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"
  ☆118Updated last year
• ashafaei / OD-test
  OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
  ☆62Updated last year
• ricvolpi / generalize-unseen-domains
  Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018
  ☆121Updated 4 years ago
• benathi / fastswa-semi-sup
  Improving Consistency-Based Semi-Supervised Learning with Weight Averaging
  ☆185Updated 6 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 2 years ago
• jfc43 / robust-ood-detection
  Robust Out-of-distribution Detection in Neural Networks
  ☆72Updated 2 years ago
• thuml / Deep-Embedded-Validation
  Code release for Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation (ICML 2019)
  ☆63Updated 5 years ago
• yulongwang12 / visual-attribution
  Pytorch Implementation of recent visual attribution methods for model interpretability
  ☆145Updated 4 years ago
• perrying / realistic-ssl-evaluation-pytorch
  Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"
  ☆80Updated 4 years ago
• YU1ut / Ensemble-of-Leave-out-Classifiers
  Code for "Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers"
  ☆27Updated 2 years ago
• RuiShu / dirt-t
  A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)
  ☆175Updated 6 years ago
• kibok90 / iccv2019-inc
  ICCV 2019 Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild
  ☆79Updated 2 years ago
• uoguelph-mlrg / confidence_estimation
  Learning Confidence for Out-of-Distribution Detection in Neural Networks
  ☆268Updated 6 years ago
• google-research / s4l
  Tensorflow implementation of S4L: Self-Supervised Semi-Supervised Learning
  ☆95Updated 5 years ago
• mmazeika / glc
  Gold Loss Correction
  ☆86Updated 6 years ago
• udibr / noisy_labels
  TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER
  ☆118Updated 7 years ago
• P2333 / Max-Mahalanobis-Training
  Max Mahalanobis Training (ICML 2018 + ICLR 2020)
  ☆90Updated 4 years ago
• toantm / BGADL
  Pytorch implementation of the paper Bayesian Generative Active Deep Learning (ICML 2019).
  ☆24Updated 5 years ago
• stanford-futuredata / sinkhorn-label-allocation
  Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…
  ☆53Updated 3 years ago
• 9310gaurav / virtual-adversarial-training
  Pytorch implementation of Virtual Adversarial Training
  ☆133Updated 5 years ago
• btjhjeon / IMM_tensorflow
  Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)
  ☆34Updated 7 years ago
• Britefury / self-ensemble-visual-domain-adapt
  Code repository for the small image experiments our paper 'Self-ensembling for Domain Adaptation'
  ☆193Updated 5 years ago
• giorgiop / loss-correction
  Robust loss functions for deep neural networks (CVPR 2017)
  ☆91Updated 4 years ago
• yueatsprograms / uda_release
  Unsupervised Domain Adaptation through Self-Supervision
  ☆79Updated 3 years ago