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/qcwthu/lifelong-fewshot-language-learning

공식 코드

LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5

https://github.com/qcydm/dids-mfl

공식 코드

3D-IDS: Doubly Disentangled Dynamic Intrusion Detection

https://github.com/qdo1010/SRPM_GPM

공식 코드

A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract Reasoning

https://github.com/qgao21/corediff

공식 코드

CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization

https://github.com/qili111/nr-rec-fus

공식 코드

Nonrigid Reconstruction of Freehand Ultrasound without a Tracker

https://github.com/qinhsiu/mclrec

공식 코드

Meta-optimized Contrastive Learning for Sequential Recommendation

https://github.com/qiqi-helloworld/absgd

공식 코드

Attentional-Biased Stochastic Gradient Descent

https://github.com/qityy/droppatch

공식 코드

Enhancing Masked Time-Series Modeling via Dropping Patches

https://github.com/qiu-hongxiang-david/gamma-minimax-learning

공식 코드

Adversarial Meta-Learning of Gamma-Minimax Estimators That Leverage Prior Knowledge

https://github.com/qiushisun/bbt-rgb

공식 코드

Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives

https://github.com/qiyanhero/tdsnet

공식 코드

A Task-aware Dual Similarity Network for Fine-grained Few-shot Learning

https://github.com/qizhongtan/d2st-adapter

공식 코드

D$^2$ST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action Recognition

https://github.com/qjay612/meta_learning_NL2SQL

공식 코드

Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learning

https://github.com/qqsuhao/One-shot-Learning-with-Absolute-Genelization

공식 코드

One-shot Learning with Absolute Generalization

https://github.com/quantum-jwjae/rl2lqs

공식 코드

Reinforcement learning to learn quantum states for Heisenberg scaling accuracy

https://github.com/quiil/benchmarkingpathologyfoundationmodels

공식 코드

Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios

https://github.com/radrumond/Chameleon

공식 코드

Chameleon: Learning Model Initializations Across Tasks With Different Schemas

https://github.com/radrumond/hidra

공식 코드

HIDRA: Head Initialization across Dynamic targets for Robust Architectures

https://github.com/rafa-zy/sent

공식 코드

Learning to Detect Noisy Labels Using Model-Based Features

https://github.com/raflaf/few-and-fewer

공식 코드

Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes

https://github.com/raflaf/fsl-benchmark-again

공식 코드

Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning

https://github.com/rahular/robust-maml

공식 코드

Minimax and Neyman-Pearson Meta-Learning for Outlier Languages

https://github.com/rahulvigneswaran/tailcalibx

공식 코드

Feature Generation for Long-tail Classification

https://github.com/rajarshd/CBR-AKBC

공식 코드

A Simple Approach to Case-Based Reasoning in Knowledge Bases

https://github.com/rajiv1990/DEff-GAN-Data-Efficient-GAN

공식 코드

DEff-GAN: Diverse Attribute Transfer for Few-Shot Image Synthesis

https://github.com/rakshitha123/WeeklyForecasting

공식 코드

An Accurate and Fully-Automated Ensemble Model for Weekly Time Series Forecasting

https://github.com/raldir/aut-few

공식 코드

Automated Few-shot Classification with Instruction-Finetuned Language Models

https://github.com/rangewing/metaweather

공식 코드

MetaWeather: Few-Shot Weather-Degraded Image Restoration

https://github.com/raoyongming/CAL

공식 코드

Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

https://github.com/raphael-baena/FIERCE-repo

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Preserving Fine-Grain Feature Information in Classification via Entropic Regularization

https://github.com/raphischer/xpcr

공식 코드

AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting

https://github.com/rashindrie/dipa

공식 코드

Discriminative Sample-Guided and Parameter-Efficient Feature Space Adaptation for Cross-Domain Few-Shot Learning

https://github.com/rasmusbergpalm/hebbian-evolution

공식 코드

Testing the Genomic Bottleneck Hypothesis in Hebbian Meta-Learning

https://github.com/raynbowy23/fedmeta-geolane

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Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection

https://github.com/rayneholland/collabdm

공식 코드

One-Shot Collaborative Data Distillation

https://github.com/rayruibochen/dpml

공식 코드

Stock Trading Volume Prediction with Dual-Process Meta-Learning

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