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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/Aryal007/glacier_mapping

공식 코드

Boundary Aware U-Net for Glacier Segmentation

https://github.com/Captain-Hong/UDA-via-joint-adversarial-learning-and-self-learning

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Unsupervised domain adaptation for cross-modality liver segmentation via joint adversarial learning and self-learning

https://github.com/Emma1066/Self-Improve-Zero-Shot-NER

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Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models

https://github.com/HDFengChina/How-to-Control-Hydrodynamic-Force

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How to Control Hydrodynamic Force on Fluidic Pinball via Deep Reinforcement Learning

https://github.com/HIT-SMC/DRL_solver

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General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learning

https://github.com/Hydragon516/PMN

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Unsupervised Video Object Segmentation via Prototype Memory Network

https://github.com/IBM/transition-amr-parser

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Pushing the Limits of AMR Parsing with Self-Learning

https://github.com/JimyZ13/ADDRESS

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Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic

https://github.com/KhaLee2307/StrDA

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Stratified Domain Adaptation: A Progressive Self-Training Approach for Scene Text Recognition

https://github.com/LAi1997/MIPlain

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Beneficial and Harmful Explanatory Machine Learning

https://github.com/LeiTian-qj/CMMS

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Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning

https://github.com/Panda-Peter/visda2019-multisource

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Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019

https://github.com/Panda-Peter/visda2019-semisupervised

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Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019

https://github.com/RPD123-byte/Demonstrating-the-Continual-Learning-Capabilities-and-Practical-Application-of-Discrete-Time-Active

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Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active Inference

https://github.com/RameshaKaru/devi

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DEVI: Open-source Human-Robot Interface for Interactive Receptionist Systems

https://github.com/VeritasXu/Ternary-Federated

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Ternary Compression for Communication-Efficient Federated Learning

https://github.com/airi-institute/al_ats

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Active Learning for Abstractive Text Summarization

https://github.com/amsterdam-internships/self-learning-traffic-lights

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Back to Basics: Deep Reinforcement Learning in Traffic Signal Control

https://github.com/ann-w/towards-a-deeper-understanding-of-reasoning-capabilities-in-large-language-models

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Towards a Deeper Understanding of Reasoning Capabilities in Large Language Models

https://github.com/anonuser4213/oeis-synthesis

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Learning Program Synthesis for Integer Sequences from Scratch

https://github.com/artetxem/vecmap

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A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings

https://github.com/ashfarhangi/Protoformer

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Protoformer: Embedding Prototypes for Transformers

https://github.com/attaullah/Self-training/blob/master/Transfer_learning.md

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Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification

https://github.com/attaullah/downsampled-plant-disease-dataset

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Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image Classification

https://github.com/ayushraina10/sgts

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Learning to design without prior data: Discovering generalizable design strategies using deep learning and tree search

https://github.com/barakeel/oeis-synthesis

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Learning Program Synthesis for Integer Sequences from Scratch

https://github.com/bethgelab/robustness

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If your data distribution shifts, use self-learning

https://github.com/bupt-ai-cz/Meta-SelfLearning

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Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

https://github.com/cambridgeltl/contrastivebli

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Improving Word Translation via Two-Stage Contrastive Learning

https://github.com/ceciliavision/zoom-learn-zoom

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Real-World Single Image Super-Resolution: A Brief Review

https://github.com/chuanxinggeng/ossl

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Dynamic Against Dynamic: An Open-set Self-learning Framework

https://github.com/copenlu/sufficient_facts

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Fact Checking with Insufficient Evidence

https://github.com/cugbbaiyun/hgcn-mix

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Cooperative Multi-Agent Reinforcement Learning with Hypergraph Convolution

https://github.com/cuiyx1720/awesome-cot4ad

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Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects

https://github.com/cvblab/self_learning_wsi_prostate

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Self-learning for weakly supervised Gleason grading of local patterns

https://github.com/cvc-lab/rse_rl

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Reinforcement Learning of Self Enhancing Camera Image and Signal Processing

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