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RESEARCH PAPER · Physical Review Research · 2022

Learning the crystal structure genome for property classification

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6 direct citing papers in this saved network. Explore the next layer with second-order citations.

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Learning the crystal structure genome for property classificationOriginalDuality at Classical Electrodynamics and its Interpretation through Machine Learning Algorithms1EXPLORING THERMAL TRANSPORT IN ELECTROCHEMICAL ENERGY STORAGE SYSTEMS UTILIZING TWO-DIMENSIONAL MATERIALS: PROSPECTS AND HURDLES2Automated crystal system identification from electron diffraction patterns using multiview opinion fusion machine learning28Boosting–Crystal Graph Convolutional Neural Network for Predicting Highly Imbalanced Data: A Case Study for Metal–Insulator Transition Materials5Capturing long-range interactions with a reciprocal-space neural network1AI-Driven Materials Genome: Accelerated Discovery of Multi-Functional Sensing Materials0

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  1. Duality at Classical Electrodynamics and its Interpretation through Machine Learning Algorithms

    International Journal of Advanced Computer Science and Applications · 2022-01-01

    Huber Nieto–Chaupis

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  2. EXPLORING THERMAL TRANSPORT IN ELECTROCHEMICAL ENERGY STORAGE SYSTEMS UTILIZING TWO-DIMENSIONAL MATERIALS: PROSPECTS AND HURDLES

    Annual Reviews of Heat Transfer · 2023-01-01

    Dibakar Datta, Eon Soo Lee

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  3. Automated crystal system identification from electron diffraction patterns using multiview opinion fusion machine learning

    Proceedings of the National Academy of Sciences · 2023-11-09

    Jie Chen, Hengrui Zhang, Carolin B. Wahl, Wei Liu, Chad Alexander Mirkin, Vinayak P. Dravid, Daniel W. Apley, Wei Chen

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  4. Boosting–Crystal Graph Convolutional Neural Network for Predicting Highly Imbalanced Data: A Case Study for Metal–Insulator Transition Materials

    ACS Applied Materials & Interfaces · 2024-08-09

    Eun Ho Kim, Jun Hyeong Gu, Jun Ho Lee, Seong Hun Kim, Jaeseon Kim, Hyo Gyeong Shin, Shin Hyun Kim, Donghwa Lee

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  5. Capturing long-range interactions with a reciprocal-space neural network

    Physical review. B./Physical review. B · 2026-04-09

    Ruijie Guo, Hongyu Yu, Liangliang Hong, Shiyou Chen, Xingao Gong, Hongjun Xiang

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  6. AI-Driven Materials Genome: Accelerated Discovery of Multi-Functional Sensing Materials

    Unknown journal · 2026-05-01

    Farzane Hasheminia, Sadegh Sadeghzadeh, Behrouz Minaei Bidgoli

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