Papers with Code 아카이브

Meta-Learning

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하위 태스크: 3
평가표: 4
보존된 평가 기록: 13

Meta-learning is a methodology considered with "learning to learn" machine learning algorithms.

<span style="color:grey; opacity: 0.6">( Image credit: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks )</span>

코드

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

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

공식 코드

Improved Visually Prompted Keyword Localisation in Real Low-Resource Settings

https://github.com/LeapLabTHU/LearnableISDA

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Fine-grained Recognition with Learnable Semantic Data Augmentation

https://github.com/Learning-and-Intelligent-Systems/Analytical-Learning-Theory

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Generalization in Machine Learning via Analytical Learning Theory

https://github.com/Learning-and-Intelligent-Systems/DualCutout

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Generalization in Machine Learning via Analytical Learning Theory

https://github.com/LeonResearch/NPGNN

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How Neural Processes Improve Graph Link Prediction

https://github.com/Li-Wanhua/MetaAge

공식 코드

MetaAge: Meta-Learning Personalized Age Estimators

https://github.com/LiJunnan1992/MLNT

공식 코드

Learning to Learn from Noisy Labeled Data

https://github.com/LiheYoung/MiningFSS

공식 코드

Mining Latent Classes for Few-shot Segmentation

https://github.com/Lirain21/UniMatch

공식 코드

UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery

https://github.com/Littleor/Personalized-DMER

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Personalized Dynamic Music Emotion Recognition with Dual-Scale Attention-Based Meta-Learning

https://github.com/LouieYang/MCL

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Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification

https://github.com/LucasAlegre/mbcd

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Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection

https://github.com/MAN-author/MAN

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Multi-Pretext Attention Network for Few-shot Learning with Self-supervision

https://github.com/MC-BERT/MC-BERT

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MC-BERT: Efficient Language Pre-Training via a Meta Controller

https://github.com/MCG-NJU/AWT

공식 코드

AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation

https://github.com/ML-GSAI/Revisiting-Dis-vs-Gen-Classifiers

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Revisiting Discriminative vs. Generative Classifiers: Theory and Implications

https://github.com/MSiam/AdaptiveMaskedProxies

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Adaptive Masked Proxies for Few-Shot Segmentation

https://github.com/MaLeLabTs/GPFormulasInterpretability

공식 코드

Learning a Formula of Interpretability to Learn Interpretable Formulas

https://github.com/Maluuba/jumping-task

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Learning Invariances for Policy Generalization

https://github.com/MaxZanella/transduction-for-vlms

공식 코드

Boosting Vision-Language Models with Transduction

https://github.com/McGill-NLP/latent-translation

공식 코드

Modelling Latent Translations for Cross-Lingual Transfer

https://github.com/MegviiDetection/FSCE

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FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding

https://github.com/MehdiKhamassi/SocialMetaLearning

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Active exploration in parameterized reinforcement learning

https://github.com/Meta-Portrait/MetaPortrait

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MetaPortrait: Identity-Preserving Talking Head Generation with Fast Personalized Adaptation

https://github.com/Michael-Tanzer/BERT-mem-lowres

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Memorisation versus Generalisation in Pre-trained Language Models

https://github.com/Microsoft/PointerSQL

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Natural Language to Structured Query Generation via Meta-Learning

https://github.com/MilanShao/AutoML-for-Multi-Class-Anomaly-Compensation-of-Sensor-Drift

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AutoML for Multi-Class Anomaly Compensation of Sensor Drift

https://github.com/MingruiLiu-ML-Lab/Single-Loop-bilevel-Optimizer-under-Unbounded-Smoothness

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A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness

https://github.com/ModelOriented/metaMIMIC

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Consolidated learning -- a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IV

https://github.com/MrtnMndt/meta-learning-CODEBRIM

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Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset

https://github.com/Mukaffi28/Bengali-Political-Sentiment-Analysis

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Motamot: A Dataset for Revealing the Supremacy of Large Language Models over Transformer Models in Bengali Political Sentiment Analysis

https://github.com/MyChocer/KGTN

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Knowledge Graph Transfer Network for Few-Shot Recognition

https://github.com/NLP2CT/Meta-Curriculum

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Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation

https://github.com/NUST-Machine-Intelligence-Laboratory/dmbfgvr

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Data-driven Meta-set Based Fine-Grained Visual Classification

https://github.com/NVIDIA/audio-flamingo

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Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities

https://github.com/NVlabs/few_shot_gaze

공식 코드

Few-Shot Adaptive Gaze Estimation

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