imtiazziko / SLK-few-shotLinks
Clustering for Few-shot Learning
☆13Updated 11 months ago
Alternatives and similar repositories for SLK-few-shot
Users that are interested in SLK-few-shot are comparing it to the libraries listed below
Sorting:
- ☆15Updated 2 years ago
- Official code for the paper "Self-Supervised Prototypical Transfer Learning for Few-Shot Classification"☆51Updated 3 years ago
- ☆27Updated 3 years ago
- (NeurIPS 2021) Realistic Evaluation of Transductive Few-Shot Learning☆24Updated 2 years ago
- Official repository of the paper 'Essentials for Class Incremental Learning'☆40Updated 3 years ago
- A non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification☆59Updated 2 years ago
- ☆29Updated 3 years ago
- Code for the paper "Selecting Relevant Features from a Universal Representation for Few-shot Classification"☆41Updated 4 years ago
- Few-shot learning with mislabeled support samples☆43Updated 2 years ago
- (NeurIPS 2020) Transductive Information Maximization for Few-Shot Learning https://arxiv.org/abs/2008.11297☆122Updated 2 years ago
- Meta-Album meta-dataset for few-shot image classification☆24Updated 2 years ago
- ☆31Updated 4 years ago
- Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/211…☆50Updated 2 years ago
- PyTorch code for the IJCNN'21 paper: "Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer"☆14Updated 2 years ago
- ☆64Updated 3 years ago
- Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data☆13Updated 2 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated last year
- This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer☆40Updated 3 years ago
- GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning☆34Updated 3 years ago
- ☆14Updated 2 years ago
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 4 years ago
- The original code for the paper "Benchmarks for Continual Few-Shot Learning".☆35Updated 4 years ago
- [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels☆34Updated 4 years ago
- [CVPR 2022] What Matters For Meta-Learning Vision Regression Tasks?☆21Updated 3 years ago
- Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples…☆58Updated 2 years ago
- PyTorch implementation for our paper EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels☆28Updated 4 years ago
- (L2ID@CVPR2021, TNNLS2022) Boosting Co-teaching with Compression Regularization for Label Noise☆48Updated 2 years ago
- Codebase for the paper titled "Continual learning with local module selection"☆25Updated 3 years ago
- Experiments on meta-learning algorithms to solve few-shot domain adaptation☆10Updated 3 years ago
- Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch☆53Updated 4 years ago