UCSC-REAL / SelfSup_NoisyLabel
Learning from noisy labels via regularization between representations
☆11Updated last year
Alternatives and similar repositories for SelfSup_NoisyLabel:
Users that are interested in SelfSup_NoisyLabel are comparing it to the libraries listed below
- Code for our NeurIPS 2022 (spotlight) paper 'Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation'☆66Updated last month
- [ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network☆19Updated 2 years ago
- Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'☆73Updated 2 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆36Updated 3 years ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆75Updated 3 years ago
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆25Updated last year
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆90Updated 2 years ago
- Code for the paper: "Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning"☆24Updated 3 years ago
- Benchmarks for semi-supervised domain generalization.☆68Updated 2 years ago
- code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"☆79Updated 11 months ago
- ☆14Updated 2 years ago
- ☆46Updated last year
- ☆13Updated last year
- ☆43Updated 3 years ago
- This repository is an unofficial implementation in PyTorch for Learning to Generate Novel Domains for Domain Generalization☆21Updated 3 years ago
- Source code for the NeurIPS 2022 Spotlight paper: "Unified Optimal Transport Framework for Universal Domain Adaptation"☆58Updated 2 years ago
- Human annotated noisy labels for CIFAR-10 and CIFAR-100. The website of CIFAR-N is available at http://www.noisylabels.com/.☆172Updated last year
- Sample Prior Guided Robust Model Learning to Suppress Noisy Labels☆31Updated 2 years ago
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 4 years ago
- "Towards Realistic Semi-Supervised Learning" by Mamshad Nayeem Rizve, Navid Kardan, Mubarak Shah (ECCV 2022)☆39Updated last year
- code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'☆103Updated 2 years ago
- The official implementation of CVPR2023 paper "DISC: Learning from Noisy Labels via Dynamic Instance-Specific Selection and Correction"☆42Updated last year
- Source code for NeurIPS 2022 paper SoLar☆27Updated last year
- Official Implementation of LADS (Latent Augmentation using Domain descriptionS)☆49Updated last year
- Multi-level Consistency Learning for Semi-supervised Domain Adaptation, IJCAI 2022☆14Updated 2 years ago
- A list of awesome partial-label learning papers and codes.☆36Updated last year
- This is the official repo for our CVPR22 paper: Scalable Penalized Regression for Noise Detection in Learning With Noisy Labels.☆18Updated 10 months ago
- ☆34Updated 11 months ago
- NN 2023☆21Updated 2 years ago
- This code accompanies the paper "Parameter-free Online Test-time Adaptation".☆67Updated 2 years ago