ZhenWang-PhD / Training-Noise-Robust-Deep-Neural-Networks-via-Meta-Learning
Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’
☆20Updated 4 years ago
Alternatives and similar repositories for Training-Noise-Robust-Deep-Neural-Networks-via-Meta-Learning:
Users that are interested in Training-Noise-Robust-Deep-Neural-Networks-via-Meta-Learning are comparing it to the libraries listed below
- This repository is an unofficial implementation in PyTorch for Learning to Generate Novel Domains for Domain Generalization☆21Updated 3 years ago
- code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'☆103Updated 2 years ago
- Code for our ECCV paper -- "Learning to Balance Specificity and Invariance for In and Out of Domain Generalization"☆54Updated 4 years ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆75Updated 3 years ago
- Official implementation for: "Multi-Objective Interpolation Training for Robustness to Label Noise"☆39Updated 2 years ago
- Code accompanying "Adaptive Methods for Aggregated Domain Generalization"☆18Updated 3 years ago
- ☆58Updated last year
- ☆59Updated 2 years ago
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆91Updated 2 years ago
- ☆43Updated 3 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆43Updated 2 years ago
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆46Updated last year
- code for our TPAMI 2021 paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"☆114Updated last year
- This repository provides code for the paper ---- On Universal Black-Box Domain Adaptation.☆10Updated 3 years ago
- Unsupervised Domain Adaptation without Source Data by Casting a BAIT☆24Updated 2 years ago
- Code for the paper "Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning" (NeurIPS 20)☆73Updated 2 years ago
- ☆46Updated last year
- Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'☆74Updated 2 years ago
- Benchmarks for semi-supervised domain generalization.☆68Updated 2 years ago
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆25Updated last year
- [AAAI 21] Utilizing meta-learning to correct the noisy labels.☆13Updated 3 years ago
- Code for 'Joint Optimization Framework for Learning with Noisy Labels'☆38Updated 6 years ago
- "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).☆50Updated 4 years ago
- This is the repo for the paper "Episodic Training for Domain Generalization" https://arxiv.org/abs/1902.00113☆57Updated last year
- ☆37Updated 3 years ago
- PyTorch code for Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings (ICCV 2021)☆42Updated last year
- ☆29Updated 3 years ago
- ☆11Updated 3 years ago
- ☆6Updated 3 years ago
- Tensorflow Implementation on Paper [AAAI2020]Semi-Supervised Learning under Class Distribution Mismatch☆15Updated 3 years ago