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Few-Shot Learning

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하위 태스크: 12
평가표: 27
보존된 평가 기록: 52

Few-Shot Learning is an example of meta-learning, where a learner is trained on several related tasks, during the meta-training phase, so that it can generalize well to unseen (but related) tasks with just few examples, during the meta-testing phase. An effective approach to the Few-Shot Learning problem is to learn a common representation for various tasks and train task specific classifiers on top of this representation.

Source: Penalty Method for Inversion-Free Deep Bilevel Optimization

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Haoqing-Wang/CDFSL-ATA

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Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

https://github.com/Haoqing-Wang/FSLSTM

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Few-shot Learning with LSSVM Base Learner and Transductive Modules

https://github.com/HeatherJiaZG/SuperGlue-pytorch

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Physarum Powered Differentiable Linear Programming Layers and Applications

https://github.com/Helsinki-NLP/Tatoeba-Challenge

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The Tatoeba Translation Challenge -- Realistic Data Sets for Low Resource and Multilingual MT

https://github.com/HenryPengZou/DeCrisisMB

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CrisisMatch: Semi-Supervised Few-Shot Learning for Fine-Grained Disaster Tweet Classification

https://github.com/Hippogriff/prifit

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PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation

https://github.com/HobbitLong/SupContrast

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Rethinking the Sample Relations for Few-Shot Classification

https://github.com/Homagn/Few_shot_clustering

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Few shot clustering for indoor occupancy detection with extremely low-quality images from battery free cameras

https://github.com/HzFu/COVID19_imaging_AI_paper_list

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Towards Data-Efficient Learning: A Benchmark for COVID-19 CT Lung and Infection Segmentation

https://github.com/Hzfinfdu/MPMP

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Multitask Pre-training of Modular Prompt for Chinese Few-Shot Learning

https://github.com/IBM/nl2bash-eabench

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Execution-Based Evaluation of Natural Language to Bash and PowerShell for Incident Remediation

https://github.com/INK-USC/CLIF

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Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning

https://github.com/INK-USC/CrossFit

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CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP

https://github.com/IRVLUTD/FewSOL-DataLoader

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FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IRVLUTD/Proto-CLIP

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Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning

https://github.com/IRVLUTD/fewsol-toolkit

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FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IRVLUTD/meta-dataset

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FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IU-SAIGE/contrastive_mixtures

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Self-Supervised Learning from Contrastive Mixtures for Personalized Speech Enhancement

https://github.com/IdanAchituve/GP-Tree

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GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning

https://github.com/IraKorshunova/bruno

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BRUNO: A Deep Recurrent Model for Exchangeable Data

https://github.com/IreneZihuiLi/TopicAttentionMedicalAD

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A Neural Topic-Attention Model for Medical Term Abbreviation Disambiguation

https://github.com/JBall1/Few-Shot-Limited-Data

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Few-Shot Learning for Image Classification of Common Flora

https://github.com/Jarvis73/FPTransPaddle

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Feature-Proxy Transformer for Few-Shot Segmentation

https://github.com/Jia-Research-Lab/PFENet

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Prior Guided Feature Enrichment Network for Few-Shot Segmentation

https://github.com/JoyHuYY1412/LST_LVIS

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Learning to Segment the Tail

https://github.com/KEAML-JLU/SMILE

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Dual-level Mixup for Graph Few-shot Learning with Fewer Tasks

https://github.com/Kayzaks/VividNet

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A Neural-Symbolic Architecture for Inverse Graphics Improved by Lifelong Meta-Learning

https://github.com/KhrulkovV/hyperbolic-image-embeddings

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Hyperbolic Image Embeddings

https://github.com/KyraZzz/nlp-prompt-attack

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Revisiting Automated Prompting: Are We Actually Doing Better?

https://github.com/LIUYUANWEI98/NERTNet

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Learning Non-target Knowledge for Few-shot Semantic Segmentation

https://github.com/LONGXUANX/CDFormer_code

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CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature Confusion

https://github.com/Layjins/CECNet

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Clustered-patch Element Connection for Few-shot Learning

https://github.com/Layjins/FewShotLearning-tSF

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tSF: Transformer-based Semantic Filter for Few-Shot Learning

https://github.com/Layjins/SpatialFormer

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SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning

https://github.com/LeanneNortje/direct_multimodal_few-shot_learning

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Direct multimodal few-shot learning of speech and images

https://github.com/LeanneNortje/low-resource_VPKL

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Improved Visually Prompted Keyword Localisation in Real Low-Resource Settings

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