Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning von Zhang, Ansi, Li, Shaobo, Cui, Yuxin, Yang, Wanli, Dong, Rongzhi, Hu, Jianjun

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Inverse design of composite metal oxide optical materials based on deep transfer learning and global optimization von Dong, Rongzhi, Dan, Yabo, Li, Xiang, Hu, Jianjun

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Mlatticeabc: Generic Lattice Constant Prediction of Crystal Materials Using Machine Learning von Li, Yuxin, Yang, Wenhui, Dong, Rongzhi, Hu, Jianjun

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Scalable deeper graph neural networks for high-performance materials property prediction von Omee, Sadman Sadeed, Louis, Steph-Yves, Fu, Nihang, Wei, Lai, Dey, Sourin, Dong, Rongzhi, Li, Qinyang, Hu, Jianjun

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Machine Learning-Based Prediction of Crystal Systems and Space Groups from Inorganic Materials Compositions von Zhao, Yong, Cui, Yuxin, Xiong, Zheng, Jin, Jing, Liu, Zhonghao, Dong, Rongzhi, Hu, Jianjun

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Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning von Li, Shaobo, Dan, Yabo, Li, Xiang, Hu, Tiantian, Dong, Rongzhi, Cao, Zhuo, Hu, Jianjun

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Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees von Dan, Yabo, Dong, Rongzhi, Cao, Zhuo, Li, Xiang, Niu, Chengcheng, Li, Shaobo, Hu, Jianjun

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Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study von Omee, Sadman Sadeed, Fu, Nihang, Dong, Rongzhi, Hu, Ming, Hu, Jianjun

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Effect of repeated Kangaroo Mother Care on repeated procedural pain in preterm infants: A randomized controlled trial von Gao, Haixia, Xu, Guihua, Gao, Honglian, Dong, Rongzhi, Fu, Hongjie, Wang, Danwen, Zhang, Heng, Zhang, Hua

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Material transformers: deep learning language models for generative materials design von Fu, Nihang, Wei, Lai, Song, Yuqi, Li, Qinyang, Xin, Rui, Omee, Sadman Sadeed, Dong, Rongzhi, Siriwardane, Edirisuriya M Dilanga, Hu, Jianjun

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Crystal Composition Transformer: Self-Learning Neural Language Model for Generative and Tinkering Design of Materials von Wei, Lai, Li, Qinyang, Song, Yuqi, Stefanov, Stanislav, Dong, Rongzhi, Fu, Nihang, Siriwardane, Edirisuriya M D, Chen, Fanglin, Hu, Jianjun

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Discovery of 2D Materials using Transformer Network‐Based Generative Design von Dong, Rongzhi, Song, Yuqi, Siriwardane, Edirisuriya M. D., Hu, Jianjun

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Composition based crystal materials symmetry prediction using machine learning with enhanced descriptors von Li, Yuxin, Dong, Rongzhi, Yang, Wenhui, Hu, Jianjun

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Generative Design of Inorganic Compounds Using Deep Diffusion Language Models von Dong, Rongzhi, Fu, Nihang, Siriwardane, Edirisuriya M. D., Hu, Jianjun

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Materials property prediction with uncertainty quantification: A benchmark study von Varivoda, Daniel, Dong, Rongzhi, Omee, Sadman Sadeed, Hu, Jianjun

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Global Mapping of Structures and Properties of Crystal Materials von Li, Qinyang, Dong, Rongzhi, Fu, Nihang, Omee, Sadman Sadeed, Wei, Lai, Hu, Jianjun

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Crystal structure prediction of materials with high symmetry using differential evolution von Yang, Wenhui, Dilanga Siriwardane, Edirisuriya M, Dong, Rongzhi, Li, Yuxin, Hu, Jianjun

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Chaos analysis and stability control of the MEMS resonator via the type-2 sequential FNN von Zhao, Le, Luo, Shaohua, Yang, Guanci, Dong, Rongzhi

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DeepXRD, a Deep Learning Model for Predicting XRD spectrum from Material Composition von Dong, Rongzhi, Zhao, Yong, Song, Yuqi, Fu, Nihang, Omee, Sadman Sadeed, Dey, Sourin, Li, Qinyang, Wei, Lai, Hu, Jianjun

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TCSP: a Template-Based Crystal Structure Prediction Algorithm for Materials Discovery von Wei, Lai, Fu, Nihang, Siriwardane, Edirisuriya M. D., Yang, Wenhui, Omee, Sadman Sadeed, Dong, Rongzhi, Xin, Rui, Hu, Jianjun

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