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Self-Learning

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

https://github.com/data-and-decision-lab/self-improving-RL

공식 코드

Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms

https://github.com/devavrattomar/tesla

공식 코드

TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

https://github.com/end2you/end2you

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End2You -- The Imperial Toolkit for Multimodal Profiling by End-to-End Learning

https://github.com/exgc/avmust-ted

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MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream Mixup for Visual Speech Translation and Recognition

https://github.com/fergunet/SabberStone

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Optimizing Hearthstone Agents using an Evolutionary Algorithm

https://github.com/hilab-git/ugtst

공식 코드

An Uncertainty-guided Tiered Self-training Framework for Active Source-free Domain Adaptation in Prostate Segmentation

https://github.com/hritam-98/gfda-disentangled

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Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning

https://github.com/iaar-shanghai/pgrag

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Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-Learning

https://github.com/ibm/amr-annotations

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Maximum Bayes Smatch Ensemble Distillation for AMR Parsing

https://github.com/ibm/retrieval-table-augmentation

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Retrieval-Based Transformer for Table Augmentation

https://github.com/isahhin/cvabs

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CVABS: Moving Object Segmentation with Common Vector Approach for Videos

https://github.com/ivulic/panlex-bli

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Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?

https://github.com/jianlin-cheng/DRLComplex

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DRLComplex: Reconstruction of protein quaternary structures using deep reinforcement learning

https://github.com/jiyuuchc/lacss

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Point-supervised Single-cell Segmentation via Collaborative Knowledge Sharing

https://github.com/jiyuuchc/lacss_jax

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Point-supervised Single-cell Segmentation via Collaborative Knowledge Sharing

https://github.com/job-sdf/benchmark

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Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking

https://github.com/johannes-dornheim/Reinforce-FE

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Model-Free Adaptive Optimal Control of Episodic Fixed-Horizon Manufacturing Processes using Reinforcement Learning

https://github.com/junjun-yan/st-pinn

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ST-PINN: A Self-Training Physics-Informed Neural Network for Partial Differential Equations

https://github.com/kumar-shridhar/smart

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SMART: Self-learning Meta-strategy Agent for Reasoning Tasks

https://github.com/kw01sg/crda

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Consistency Regularization for Domain Adaptation

https://github.com/lamsieh/DQN

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Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion Detection

https://github.com/leeguandong/SGDSCNet-for-HSI

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Spatial-Geometry Enhanced 3D Dynamic Snake Convolutional Neural Network for Hyperspectral Image Classification

https://github.com/liuzh-19/esg

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Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

https://github.com/lizheren/MSVCL_MICCAI2021

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Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning

https://github.com/lizzy8587/castdet

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Toward Open Vocabulary Aerial Object Detection with CLIP-Activated Student-Teacher Learning

https://github.com/ll0ruc/AutoMIR

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AutoMIR: Effective Zero-Shot Medical Information Retrieval without Relevance Labels

https://github.com/lxucs/multilingual-sl

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Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation

https://github.com/lzqw/c-hac

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Confidence-Guided Human-AI Collaboration: Reinforcement Learning with Distributional Proxy Value Propagation for Autonomous Driving

https://github.com/marszhaoyt/sslchange

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SSLChange: A Self-supervised Change Detection Framework Based on Domain Adaptation

https://github.com/materialsvirtuallab/maml

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Discovery of 2D materials using Transformer Network based Generative Design

https://github.com/microsoft/seed-encoder

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Less is More: Pre-train a Strong Text Encoder for Dense Retrieval Using a Weak Decoder

https://github.com/moothes/a2s-v2

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Texture-guided Saliency Distilling for Unsupervised Salient Object Detection

https://github.com/nailwatts/fnin

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FNIN: A Fourier Neural Operator-based Numerical Integration Network for Surface-form-gradients

https://github.com/ngarneau/vecmap

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A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well

https://github.com/niuchuangnn/GATCluster

공식 코드

GATCluster: Self-Supervised Gaussian-Attention Network for Image Clustering

https://github.com/njustkmg/ssoc

공식 코드

Robust Semi-Supervised Learning for Self-learning Open-World Classes

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.