danieltan07 / learning-to-reweight-examplesLinks
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
☆353Updated 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☆295Updated 6 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆290Updated 3 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆507Updated 3 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆223Updated 4 years ago
- Learning What and Where to Transfer (ICML 2019)☆248Updated 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
- Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks☆323Updated 2 years ago
- Meta-Learning based Noise-Tolerant Training☆126Updated 4 years ago
- Learning deep representations by mutual information estimation and maximization☆324Updated 6 years ago
- Code for reproducing Manifold Mixup results (ICML 2019)☆493Updated last year
- TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER☆118Updated 8 years ago
- ☆175Updated 11 months ago
- Code for ICLR19 paper: Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning.☆243Updated 6 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆186Updated 6 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆182Updated 5 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆128Updated 5 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆147Updated 4 years ago
- Learning Confidence for Out-of-Distribution Detection in Neural Networks☆275Updated 7 years ago
- Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"☆257Updated 7 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆176Updated 3 years ago
- Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning☆120Updated 11 months ago
- Gold Loss Correction☆87Updated 6 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆234Updated 3 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆85Updated 6 years ago
- Tensorflow implementation of "Learning to Balance: Bayesian Meta-learning for Imbalanced and Out-of-distribution Tasks" (ICLR 2020 oral)☆101Updated 4 years ago
- Reproduction of "Model-Agnostic Meta-Learning" (MAML) and "Reptile".☆193Updated 6 years ago
- This is a collection of Papers and Codes for Noisy Labels Problem.☆63Updated 7 years ago