hendrycks / error-detection
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
☆227Updated 6 years ago
Alternatives and similar repositories for error-detection:
Users that are interested in error-detection are comparing it to the libraries listed below
- Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".☆345Updated 5 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆181Updated 5 years ago
- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 5 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆69Updated 4 years ago
- Learning Confidence for Out-of-Distribution Detection in Neural Networks☆274Updated 7 years ago
- Self-Supervised Learning for OOD Detection (NeurIPS 2019)☆266Updated 4 years ago
- ☆69Updated 6 years ago
- A simple and effective method for detecting out-of-distribution images in neural networks.☆536Updated 3 years ago
- We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…☆57Updated 3 years ago
- ☆410Updated 3 years ago
- Deep Anomaly Detection with Outlier Exposure (ICLR 2019)☆557Updated 3 years ago
- Principled Detection of Out-of-Distribution Examples in Neural Networks☆201Updated 7 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Robust Out-of-distribution Detection in Neural Networks☆72Updated 3 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆129Updated 3 years ago
- Code for "Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers"☆27Updated 3 years ago
- ☆46Updated 4 years ago
- [SafeAI'21] Feature Space Singularity for Out-of-Distribution Detection.☆80Updated 4 years ago
- Robust loss functions for deep neural networks (CVPR 2017)☆91Updated 4 years ago
- Pytorch implementation of Virtual Adversarial Training☆134Updated 5 years ago
- Gold Loss Correction☆87Updated 6 years ago
- Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆80Updated 4 years ago
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆56Updated 2 years ago
- Description Code for the paper "Robust Inference via Generative Classifiers for Handling Noisy Labels".☆32Updated 5 years ago
- CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)☆281Updated last year
- ☆175Updated 9 months ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆126Updated 5 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆90Updated 4 years ago
- Source code for ICLR 2018 Paper: Active Learning for Convolutional Neural Networks: A Core-Set Approach☆271Updated 6 years ago