alinlab / Confident_classifierLinks
Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018
☆182Updated 5 years ago
Alternatives and similar repositories for Confident_classifier
Users that are interested in Confident_classifier are comparing it to the libraries listed below
Sorting:
- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 5 years ago
- Self-Supervised Learning for OOD Detection (NeurIPS 2019)☆267Updated 4 years ago
- Learning Confidence for Out-of-Distribution Detection in Neural Networks☆275Updated 7 years ago
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks☆231Updated 6 years ago
- Principled Detection of Out-of-Distribution Examples in Neural Networks☆202Updated 8 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆69Updated 4 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆186Updated 6 years ago
- Code for the paper "A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks".☆346Updated 5 years ago
- [CVPR2019]Learning Not to Learn : An adversarial method to train deep neural networks with biased data☆111Updated 5 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- Robust loss functions for deep neural networks (CVPR 2017)☆91Updated 5 years ago
- ☆129Updated 2 years ago
- Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆80Updated 5 years ago
- Gold Loss Correction☆87Updated 6 years ago
- A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)☆175Updated 7 years ago
- Meta-Learning based Noise-Tolerant Training☆126Updated 4 years ago
- ☆175Updated 11 months ago
- Pytorch implementation of Virtual Adversarial Training☆134Updated 6 years ago
- PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning☆353Updated 6 years ago
- A simple and effective method for detecting out-of-distribution images in neural networks.☆536Updated 3 years ago
- Code for "Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers"☆27Updated 3 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- Code repository for the small image experiments our paper 'Self-ensembling for Domain Adaptation'☆194Updated 5 years ago
- ☆58Updated last year
- Official Pytorch Implementation for ICML'19 paper: Unsupervised Deep Learning by Neighbourhood Discovery☆156Updated 6 years ago
- SpotTune: Transfer Learning through Adaptive Fine-tuning☆90Updated 5 years ago
- "Learning to Discover Novel Visual Categories via Deep Transfer Clustering" by Kai Han, Andrea Vedaldi, Andrew Zisserman (ICCV 2019)☆166Updated 2 years ago
- Code release for Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation (ICML 2019)☆64Updated 6 years ago