7 citations · 8 across the 4 of their papers we have counts for
4 papers
Crystal Transformer: Self-learning neural language model for Generative and Tinkering Design of Materials
Lai Wei, Qinyang Li, Yuqi Song +4
Self-supervised neural language models have recently achieved unprecedented success, from natural language processing to learning the languages of biological sequences and organic…
DeepXRD, a Deep Learning Model for Predicting of XRD spectrum from Materials Composition
Rongzhi Dong, Yong Zhao, Yuqi Song +6
One of the long-standing problems in materials science is how to predict a material's structure and then its properties given only its composition. Experimental characterization of…
Scalable deeper graph neural networks for high-performance materials property prediction
Sadman Sadeed Omee, Steph-Yves Louis, Nihang Fu +5
Machine learning (ML) based materials discovery has emerged as one of the most promising approaches for breakthroughs in materials science. While heuristic knowledge based descript…
MaterialsAtlas.org: A Materials Informatics Web App Platform for Materials Discovery and Survey of State-of-the-Art
Jianjun Hu, Stanislav Stefanov, Yuqi Song +4
The availability and easy access of large scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for mat…