danieltan07 / learning-to-reweight-examplesLinks
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
☆354Updated 6 years ago
Alternatives and similar repositories for learning-to-reweight-examples
Users that are interested in learning-to-reweight-examples are comparing it to the libraries listed below
Sorting:
- Code for paper "Learning to Reweight Examples for Robust Deep Learning"☆269Updated 6 years ago
- Virtual Adversarial Training (VAT) implementation for PyTorch☆296Updated 6 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆290Updated 3 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆224Updated 5 years ago
- Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks☆325Updated 2 years ago
- Learning What and Where to Transfer (ICML 2019)☆250Updated 5 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆517Updated 4 years ago
- Pytorch implementation of Virtual Adversarial Training☆134Updated 6 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Meta-Learning based Noise-Tolerant Training☆123Updated 5 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆188Updated 6 years ago
- Learning deep representations by mutual information estimation and maximization☆322Updated 6 years ago
- ☆178Updated last year
- Code for reproducing Manifold Mixup results (ICML 2019)☆495Updated last year
- TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER☆119Updated 8 years ago
- Learning Confidence for Out-of-Distribution Detection in Neural Networks☆276Updated 7 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆182Updated 5 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆148Updated 5 years ago
- Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning☆120Updated last year
- Gold Loss Correction☆88Updated 7 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆130Updated 6 years ago
- Temporal ensembling for semi-supervised learning☆159Updated 8 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆176Updated 3 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆90Updated 6 years ago
- Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"☆261Updated 8 years ago
- Code for ICLR19 paper: Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning.☆244Updated 6 years ago
- Robust loss functions for deep neural networks (CVPR 2017)☆92Updated 5 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning☆111Updated 7 years ago
- Virtual adversarial training with Tensorflow☆254Updated 7 years ago