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scientific discovery

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

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

https://github.com/ptrckhmmr/learning-to-defer-with-limited-expert-predictions

Differentiable Learning Under Triage

https://github.com/reginareis/doutorado

Discovering physical concepts with neural networks

https://github.com/samuelschmidgall/agentlaboratory

Agent Laboratory: Using LLM Agents as Research Assistants

https://github.com/shaozhang0115/table-extraction-for-geoscience-literature

KnowledgeShovel: An AI-in-the-Loop Document Annotation System for Scientific Knowledge Base Construction

https://github.com/sharad461/MKA-hallucination

Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers

https://github.com/simplaj/AI-Researcher-Spark

Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers

https://github.com/sreyas-mohan/electron-microscopy-denoising

Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy

https://github.com/sutoiku/autostat

Structure Discovery in Nonparametric Regression through Compositional Kernel Search

https://github.com/tom-beer/deep-scientific-discovery

Using Deep Networks for Scientific Discovery in Physiological Signals

https://github.com/ying531/conformal-selection

Selection by Prediction with Conformal p-values

https://github.com/yonesuke/GreenLearning.jl

Data-driven discovery of Green's functions with human-understandable deep learning

https://github.com/zhaoolee/garss

Robin: A multi-agent system for automating scientific discovery

https://gitlab.com/picture-production/picture-nnunet-package

Automated Design of Deep Learning Methods for Biomedical Image Segmentation

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