xjtushujun / meta-weight-netLinks
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
☆289Updated 3 years ago
Alternatives and similar repositories for meta-weight-net
Users that are interested in meta-weight-net are comparing it to the libraries listed below
Sorting:
- PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning☆354Updated 6 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆129Updated 5 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆89Updated 6 years ago
- Code for: "Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes" and "TaskNorm: Rethinking Batch Norma…☆160Updated 4 years ago
- (ECCV 2020) Cross-Domain Few-Shot Learning Benchmarking System☆231Updated 4 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆513Updated 4 years ago
- ☆177Updated last year
- SpotTune: Transfer Learning through Adaptive Fine-tuning☆91Updated 6 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆224Updated 5 years ago
- Meta-Learning based Noise-Tolerant Training☆126Updated 5 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆177Updated 3 years ago
- Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆80Updated 5 years ago
- [NeurIPS 2020] Released code for Interventional Few-Shot Learning☆169Updated 4 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆236Updated 4 years ago
- PyTorch implementation of “Negative Margin Matters: Understanding Margin in Few-shot Classification”☆152Updated 4 years ago
- Feature-Critic Networks for Heterogeneous Domain Generalisation☆53Updated 6 years ago
- ☆187Updated last month
- [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss☆686Updated 3 years ago
- ☆154Updated 5 years ago
- Learning What and Where to Transfer (ICML 2019)☆249Updated 4 years ago
- This is the official implementation of Self-Challenging Improves Cross-Domain Generalization, ECCV2020☆165Updated 4 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
- Pytorch Code for ICLR19 paper: Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning.☆177Updated 4 years ago
- "Automatically Discovering and Learning New Visual Categories with Ranking Statistics" by Kai Han, Sylvestre-Alvise Rebuffi, Sebastien Eh…☆229Updated 5 years ago
- ☆131Updated 4 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation (ICLR 2020 spotlight)☆346Updated 5 years ago
- Learning deep representations by mutual information estimation and maximization☆323Updated 6 years ago
- The demo code for the MLDG paper "Learning to Generalize: Meta-Learning for Domain Generalization", https://arxiv.org/abs/1710.03463, htt…☆147Updated 6 years ago
- [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration☆475Updated 3 years ago