wangz10 / contrastive_lossLinks
Experiments with supervised contrastive learning methods with different loss functions
☆220Updated 2 years ago
Alternatives and similar repositories for contrastive_loss
Users that are interested in contrastive_loss are comparing it to the libraries listed below
Sorting:
- NeurIPS 2020, Debiased Contrastive Learning☆283Updated 2 years ago
- Awesome Contrastive Learning for CV & NLP☆163Updated 3 years ago
- PyTorch code for "Prototypical Contrastive Learning of Unsupervised Representations"☆595Updated 2 months ago
- ICLR 2021, Contrastive Learning with Hard Negative Samples☆270Updated 3 years ago
- A collection of awesome things about mixed sample data augmentation☆132Updated 5 years ago
- Independent implementation of Supervised Contrastive Loss. Straight to the point and beyond☆81Updated 4 years ago
- Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Wei…☆112Updated 5 years ago
- Pseudo Labeling for Neural Networks and Logistic Regression/SVMs ( Based on "Pseudo-Label : The Simple and Efficient Semi-Supervised Lear…☆73Updated 5 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆153Updated 4 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆139Updated 4 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆296Updated 2 years ago
- A simple to use pytorch wrapper for contrastive self-supervised learning on any neural network☆141Updated 4 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆187Updated 4 years ago
- 📜 Self-Supervised Learning from Images: Up-to-date reading list.☆201Updated 3 years ago
- Code for the paper "Contrastive Clustering" (AAAI 2021)☆319Updated 3 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆78Updated 4 years ago
- ☆160Updated 3 weeks ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆170Updated 4 years ago
- [NeurIPS 2020] Released code for Interventional Few-Shot Learning☆169Updated 3 years ago
- A list of contrastive Learning papers☆306Updated 3 years ago
- ICLR 2021 i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning☆78Updated last year
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆128Updated 5 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆507Updated 3 years ago
- Pytorch implementation of "A Simple Framework for Contrastive Learning of Visual Representations"☆82Updated last year
- Learning deep representations by mutual information estimation and maximization☆324Updated 6 years ago
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆559Updated 4 years ago
- This repository is an implementation for the loss function proposed in https://arxiv.org/pdf/2110.06848.pdf.☆115Updated 3 years ago
- ☆415Updated 3 years ago
- Unofficial PyTorch implementation of "Meta Pseudo Labels"☆387Updated last year