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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/RamnathKumar181/Adversarial-Learning-Dynamics-in-RL

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

https://github.com/RchalYang/Soft-Module

Multi-Task Reinforcement Learning with Soft Modularization

https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection

Compact Bilinear Pooling

https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection

Learning Meta Face Recognition in Unseen Domains

https://github.com/RobvanGastel/meta-in-context-learning

General-Purpose In-Context Learning by Meta-Learning Transformers

https://github.com/RobvanGastel/meta-rl-algorithms

Learning to reinforcement learn

https://github.com/RogerQi/pascal-5i

One-Shot Learning for Semantic Segmentation

https://github.com/RossNordby/SoftPromptsForEvaluation

The Power of Scale for Parameter-Efficient Prompt Tuning

https://github.com/Runist/torch_maml

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/Ryan0v0/Google_ML_Camp

Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning

https://github.com/RyanKim17920/DeepMoE

Deep Mixture of Experts via Shallow Embedding

https://github.com/SAGNIKMJR/CODEBRIM_MetaQNN

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

https://github.com/SAP-samples/acl2022-self-contrastive-decorrelation

miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings

https://github.com/Sakura03/SemiMeta

Semi-Supervised Learning with Meta-Gradient

https://github.com/Samyu0304/thought-propagation

Language Models are Few-Shot Learners

https://github.com/Savannah120/alignment-handbook-PoFT

Zephyr: Direct Distillation of LM Alignment

https://github.com/Sean-Huang65/AUX-TS

Adaptive Transfer Learning on Graph Neural Networks

https://github.com/SeonbeomKim/TensorFlow-Matching_Networks_for_One_Shot_Learning

Matching Networks for One Shot Learning

https://github.com/Seth-Park/MultimodalExplanations

Compact Bilinear Pooling

https://github.com/ShapeAI/OneShotLearning-with-Siamese-

Generalizing from a Few Examples: A Survey on Few-Shot Learning

https://github.com/ShapeAI/OneShotLearning-with-Siamese-character_classification

Generalizing from a Few Examples: A Survey on Few-Shot Learning

https://github.com/Shawn-Inspur/Yuan-1.0

Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning

https://github.com/ShuYuHuang/LSTM-optimizer

Learning to learn by gradient descent by gradient descent

https://github.com/ShuvenduRoy/FER_TL_PipelineTraining

Consistency-guided Prompt Learning for Vision-Language Models

https://github.com/SilverQ/NER_Final

Few-shot Learning for Named Entity Recognition in Medical Text

https://github.com/SilverQ/NamedEntityRecognition

Few-shot Learning for Named Entity Recognition in Medical Text

https://github.com/SinghJasdeep/Projecting-Conflicting-Gradients

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/Soikonomou/albert_final

Matching the Blanks: Distributional Similarity for Relation Learning

https://github.com/Soikonomou/albert_final_infer12

Matching the Blanks: Distributional Similarity for Relation Learning

https://github.com/Soikonomou/albert_final_infer8

Matching the Blanks: Distributional Similarity for Relation Learning

https://github.com/Soikonomou/bert_new

Matching the Blanks: Distributional Similarity for Relation Learning

https://github.com/Soikonomou/bert_new_new

Matching the Blanks: Distributional Similarity for Relation Learning

https://github.com/SoojungYang/supervised_pretraining_GN_WS

Big Transfer (BiT): General Visual Representation Learning

https://github.com/SoongE/siamese-one-shot-pytorch

https://github.com/StanfordVL/arxivbot

Neural Task Programming: Learning to Generalize Across Hierarchical Tasks

https://github.com/SunghwanHong/Cost-Aggregation-transformers

Cost Aggregation Is All You Need for Few-Shot Segmentation

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