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/razvanalex-phd/cwi_llm

공식 코드

Investigating Large Language Models for Complex Word Identification in Multilingual and Multidomain Setups

https://github.com/rb080/wss_pole

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Prompting classes: Exploring the Power of Prompt Class Learning in Weakly Supervised Semantic Segmentation

https://github.com/redabensaidds/foundation_fewshot

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A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models

https://github.com/remiMZ/HTS-ECCV22

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Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation

https://github.com/remilepriol/causal-adaptation-speed

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An Analysis of the Adaptation Speed of Causal Models

https://github.com/remimz/metacoco-iclr24

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MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation

https://github.com/renmengye/few-shot-ssl-public

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Meta-Learning for Semi-Supervised Few-Shot Classification

https://github.com/renmengye/inc-few-shot-attractor-public

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Incremental Few-Shot Learning with Attention Attractor Networks

https://github.com/renmengye/oc-fewshot-public

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Wandering Within a World: Online Contextualized Few-Shot Learning

https://github.com/renmengye/online-unsup-proto-net

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Online Unsupervised Learning of Visual Representations and Categories

https://github.com/resibots/kaushik_2019_aprol

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Adaptive Prior Selection for Repertoire-based Online Adaptation in Robotics

https://github.com/resibots/kaushik_2020_famle

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Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated Priors

https://github.com/rezanajian/fol

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A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary Geometries

https://github.com/rezazad68/fewshot-segmentation

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On the Texture Bias for Few-Shot CNN Segmentation

https://github.com/rgmantovani/DecisionTreeTuningAnalysis

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A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiers

https://github.com/ricardoinaciopt/mast

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Meta-learning and Data Augmentation for Stress Testing Forecasting Models

https://github.com/richardaecn/dataset-granularity

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Measuring Dataset Granularity

https://github.com/richrast/spin

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Semi-Parametric Inducing Point Networks and Neural Processes

https://github.com/ricupa/mtml-learn-how-to-adapt-to-unseen-tasks

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Multi-Task Meta Learning: learn how to adapt to unseen tasks

https://github.com/riveSunder/carle

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Carle's Game: An Open-Ended Challenge in Exploratory Machine Creativity

https://github.com/rizar/CLOSURE

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CLOSURE: Assessing Systematic Generalization of CLEVR Models

https://github.com/rl-submissions/macro-credit-masp

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Meta-learning how to Share Credit among Macro-Actions

https://github.com/rl-vig/libfewshot

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LibFewShot: A Comprehensive Library for Few-shot Learning

https://github.com/rlacombe/climatex

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ClimateX: Do LLMs Accurately Assess Human Expert Confidence in Climate Statements?

https://github.com/rlqja1107/torch-LLM4SGG

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LLM4SGG: Large Language Models for Weakly Supervised Scene Graph Generation

https://github.com/rlworkgroup/metaworld

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

https://github.com/rmanluo/np-fkgc

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Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion

https://github.com/robertoshea/forward_projection

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Closed-Form Feedback-Free Learning with Forward Projection

https://github.com/roberttlange/evosax

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Discovering Evolution Strategies via Meta-Black-Box Optimization

https://github.com/robinlu1209/st-gfsl

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Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer

https://github.com/robotic-vision-lab/few-shot-fruit-segmentation-via-transfer-learning

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Few-Shot Fruit Segmentation via Transfer Learning

https://github.com/rohitrango/STNAdversarial

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MA 3 : Model Agnostic Adversarial Augmentation for Few Shot learning

https://github.com/ron-amit/meta-learning-adjusting-priors

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Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory

https://github.com/rorozhl/mmkd

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Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning

https://github.com/rose-stl-lab/dynamic-adaptation-network

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Meta-Learning Dynamics Forecasting Using Task Inference

https://github.com/rose-stl-lab/teleportation-optimization

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Improving Convergence and Generalization Using Parameter Symmetries

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