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/zhuliwen/roadnetsz

공식 코드

MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control

https://github.com/zhuyixuan1997/eegscopeandarbitration

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Window Stacking Meta-Models for Clinical EEG Classification

https://github.com/zhuyun97/graphclip

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GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs

https://github.com/zhw12/BERTRL

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Inductive Relation Prediction by BERT

https://github.com/zifengding/fitcarl

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Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs using Confidence-Augmented Reinforcement Learning

https://github.com/zihangJiang/Adaptive-Attention

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Few-shot Classification via Adaptive Attention

https://github.com/zihangm/Differentiable-LP-Layer

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Physarum Powered Differentiable Linear Programming Layers and Applications

https://github.com/zihangm/Physarum-Differentiable-LP-Layer

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Physarum Powered Differentiable Linear Programming Layers and Applications

https://github.com/zihangm/neural-tmd-layer

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Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators

https://github.com/zihanwangki/fffner

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Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity Recognition

https://github.com/zihaohe123/norm-violation-detection-prompt-based

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CPL-NoViD: Context-Aware Prompt-based Learning for Norm Violation Detection in Online Communities

https://github.com/ziqihuangg/reversion

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ReVersion: Diffusion-Based Relation Inversion from Images

https://github.com/zj-binxia/mrda

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Meta-Learning based Degradation Representation for Blind Super-Resolution

https://github.com/zjlab-ammi/q-net

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Q-Net: Query-Informed Few-Shot Medical Image Segmentation

https://github.com/zju-dbl/metakg

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MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation

https://github.com/zjukg/maker

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Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting

https://github.com/zjukg/morse

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Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding

https://github.com/zjunlp/DART

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Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners

https://github.com/zjunlp/DeepKE/tree/main/example/ner/few-shot

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LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting

https://github.com/zjunlp/PromptKG/tree/main/research/RetrievalRE

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Relation Extraction as Open-book Examination: Retrieval-enhanced Prompt Tuning

https://github.com/zoilsen/flor

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Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning

https://github.com/zoulixin93/NICF

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Neural Interactive Collaborative Filtering

https://github.com/zouxinyi0625/cdnet

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Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression Recognition

https://github.com/zpx16900/DGGN

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Edge-Labeling based Directed Gated Graph Network for Few-shot Learning

https://github.com/zrrskywalker/cafo

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Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners

https://github.com/zrrskywalker/pointclip

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PointCLIP: Point Cloud Understanding by CLIP

https://github.com/zshanggu/cdmm

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Cross-domain Multi-modal Few-shot Object Detection via Rich Text

https://github.com/zuwenqiang/ept

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Embedded Prompt Tuning: Towards Enhanced Calibration of Pretrained Models for Medical Images

https://github.com/zwfightzw/Meta-Critic

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Online Meta-Critic Learning for Off-Policy Actor-Critic Methods

https://github.com/zwzheng98/qclnet

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Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation

https://github.com/zxcvfd13502/ddas_code

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Direct Differentiable Augmentation Search

https://github.com/zyang1580/SML

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How to Retrain Recommender System? A Sequential Meta-Learning Method

https://github.com/zyn-1101/dandr

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Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal Perspective

https://github.com/zzqzzq/bml

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Binocular Mutual Learning for Improving Few-shot Classification

https://github.com/zzwdx/ARITH

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Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization

https://github.com/zzwdx/medic

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Generalizable Decision Boundaries: Dualistic Meta-Learning for Open Set Domain Generalization

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