| Scalable deeper graph neural networks for high-performance materials property prediction SS Omee, SY Louis, N Fu, L Wei, S Dey, R Dong, Q Li, J Hu Patterns 3 (5), 2022 | 60 | 2022 |
| MaterialsAtlas. org: a materials informatics web app platform for materials discovery and survey of state-of-the-art J Hu, S Stefanov, Y Song, SS Omee, SY Louis, EMD Siriwardane, Y Zhao, ... npj Computational Materials 8 (1), 65, 2022 | 30 | 2022 |
| TCSP: a Template-Based Crystal Structure Prediction Algorithm for Materials Discovery L Wei, N Fu, EMD Siriwardane, W Yang, SS Omee, R Dong, R Xin, J Hu Inorganic Chemistry, 2022 | 23 | 2022 |
| Material transformers: deep learning language models for generative materials design N Fu, L Wei, Y Song, Q Li, R Xin, SS Omee, R Dong, EMD Siriwardane, ... Machine Learning: Science and Technology 4 (1), 015001, 2023 | 12 | 2023 |
| Crystal transformer: Self-learning neural language model for generative and tinkering design of materials L Wei, Q Li, Y Song, S Stefanov, E Siriwardane, F Chen, J Hu arXiv preprint arXiv:2204.11953, 2022 | 10 | 2022 |
| DeepXRD, a deep learning model for predicting XRD spectrum from material composition R Dong, Y Zhao, Y Song, N Fu, SS Omee, S Dey, Q Li, L Wei, J Hu ACS Applied Materials & Interfaces 14 (35), 40102-40115, 2022 | 8 | 2022 |
| Probabilistic generative transformer language models for generative design of molecules L Wei, N Fu, Y Song, Q Wang, J Hu Journal of Cheminformatics 15 (1), 88, 2023 | 6 | 2023 |
| Predicting lattice vibrational frequencies using deep graph neural networks N Nguyen, SYV Louis, L Wei, K Choudhary, M Hu, J Hu ACS omega 7 (30), 26641-26649, 2022 | 4 | 2022 |
| Crystal structure prediction using neural network potential and age-fitness pareto genetic algorithm SS Omee, L Wei, M Hu, J Hu OAE Publishing Inc., 2024 | 3 | 2024 |
| Global mapping of structures and properties of crystal materials Q Li, R Dong, N Fu, SS Omee, L Wei, J Hu Journal of Chemical Information and Modeling 63 (12), 3814-3826, 2023 | 3 | 2023 |
| Predicting lattice phonon vibrational frequencies using deep graph neural networks N Nguyen, SY Louis, L Wei, K Choudhary, M Hu, J Hu arXiv preprint arXiv:2111.05885, 2021 | 3 | 2021 |
| Towards quantitative evaluation of crystal structure prediction performance L Wei, Q Li, SS Omee, J Hu Computational Materials Science 235, 112802, 2024 | 2 | 2024 |
| Materials transformers language models for generative materials design: a benchmark study N Fu, L Wei, Y Song, Q Li, R Xin, SS Omee, R Dong, EMD Siriwardane, ... arXiv preprint arXiv:2206.13578, 2022 | 2 | 2022 |
| AlphaCrystal-II: Distance matrix based crystal structure prediction using deep learning Y Song, R Dong, L Wei, Q Li, J Hu arXiv preprint arXiv:2404.04810, 2024 | | 2024 |
| Physics-Guided Dual Self-Supervised Learning for Structure-Based Material Property Prediction N Fu, L Wei, J Hu The Journal of Physical Chemistry Letters 15 (10), 2841-2850, 2024 | | 2024 |
| Evolutionary Machine Learning in Science and Engineering J Hu, Y Song, SS Omee, L Wei, R Dong, S Gianey Handbook of Evolutionary Machine Learning, 535-561, 2023 | | 2023 |
| Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm S Sadeed Omee, L Wei, J Hu arXiv e-prints, arXiv: 2309.06710, 2023 | | 2023 |
| TCSP: a Template based crystal structure prediction algorithm and web server for materials discovery L Wei, N Fu, E Siriwardane, W Yang, SS Omee, R Dong, R Xin, J Hu https://arxiv.org/abs/2111.14049, 2021 | | 2021 |
| Predicting Phonon Vibrational Frequencies Using Deep Graph Neural networks N Nguyen, SY Louis, L Wei, K Choudhary, M Hu, J Hu | | |
