anirudhshenoy / pseudo_labeling_small_datasets
Pseudo Labeling for Neural Networks and Logistic Regression/SVMs ( Based on "Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks")
☆73Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for pseudo_labeling_small_datasets
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆135Updated 3 years ago
- ☆25Updated 7 years ago
- PyTorch implementation for "Few-Shot Learning with Class Imbalance"☆35Updated 3 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆153Updated 4 years ago
- Experiments with supervised contrastive learning methods with different loss functions☆216Updated last year
- multilabel-learn: Multilabel-Classification Algorithms☆36Updated 4 years ago
- [ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gon…☆67Updated 2 years ago
- This is a PyTorch implementation of the Unsupervised Domain Adaptation method proposed in the paper Deep CORAL: Correlation Alignment for…☆51Updated 6 years ago
- A Python Package for Deep Imbalanced Learning☆54Updated last year
- Official implementation of ICLR 2020 paper Unsupervised Clustering using Pseudo-semi-supervised Learning☆48Updated 3 years ago
- Independent implementation of Supervised Contrastive Loss. Straight to the point and beyond☆76Updated 3 years ago
- Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark…☆81Updated 3 years ago
- Custom loss functions to use in (mainly) PyTorch.☆37Updated 4 years ago
- A Meta-Learning Approach for Few-Shot Anomaly Detection and One-Class Classification☆35Updated 2 years ago
- [ICML 2022] RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression☆42Updated 2 years ago
- Pytorch implementation of "DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data".☆110Updated 3 years ago
- Implementation of Few-shot Domain Adaptation by Causal Mechanism Transfer (ICML 2020)☆40Updated last year
- This is the official PyTorch implementation of the paper "Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning" (Ju He, Adam Kor…☆27Updated 3 years ago
- Imbalanced Image Classification with Complement Cross Entropy (Pytorch)☆48Updated last year
- SimMatch: Semi-supervised Learning with Similarity Matching☆90Updated 10 months ago
- ☆19Updated 4 years ago
- Codes for "Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier"☆29Updated 3 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 5 years ago
- Easy to use class balanced cross entropy and focal loss implementation for Pytorch☆89Updated last year
- TensorFlow 2 implementation of the paper Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution …☆45Updated 3 years ago
- "In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Riz…☆230Updated last year
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- A collection of awesome things about mixed sample data augmentation☆132Updated 4 years ago
- [NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题☆105Updated 5 months ago
- An implementation of "Prototypical Networks for Few-shot Learning" on a notebook in Pytorch☆55Updated 4 years ago