Nihang Fu

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 19

Top Topics

Top Venues

Mach. Learn. Sci. Technol.

J. Cheminformatics

J. Chem. Inf. Model.

Publications

Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong, Ming Hu, Jianjun Hu
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study. CoRR (2024)
Qin Li, Nihang Fu, Sadman Sadeed Omee, Jianjun Hu
MD-HIT: Machine learning for materials property prediction with dataset redundancy control. CoRR (2023)
Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Lai Wei, Jianjun Hu
Global Mapping of Structures and Properties of Crystal Materials. J. Chem. Inf. Model. 63 (12) (2023)
Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
Material transformers: deep learning language models for generative materials design. Mach. Learn. Sci. Technol. 4 (1) (2023)
Shuangjun Liu, Xiaofei Huang, Nihang Fu, Cheng Li, Zhongnan Su, Sarah Ostadabbas
Simultaneously-Collected Multimodal Lying Pose Dataset: Enabling In-Bed Human Pose Monitoring. IEEE Trans. Pattern Anal. Mach. Intell. 45 (1) (2023)
Rongzhi Dong, Nihang Fu, Dirisuriya M. D. Siriwardane, Jianjun Hu
Generative Design of inorganic compounds using deep diffusion language models. CoRR (2023)
Lai Wei, Nihang Fu, Yuqi Song, Qian Wang, Jianjun Hu
Probabilistic generative transformer language models for generative design of molecules. J. Cheminformatics 15 (1) (2023)
Nihang Fu, Jeffrey Hu, Ying Feng, Gregory Morrison, Hans-Conrad zur Loye, Jianjun Hu
Composition based oxidation state prediction of materials using deep learning. CoRR (2022)
Sadman Sadeed Omee, Steph-Yves M. Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu
Scalable deeper graph neural networks for high-performance materials property prediction. Patterns 3 (5) (2022)
Yong Zhao, Edirisuriya M. Dilanga Siriwardane, Zhenyao Wu, Ming Hu, Nihang Fu, Jianjun Hu
Physics Guided Generative Adversarial Networks for Generations of Crystal Materials with Symmetry Constraints. CoRR (2022)
Xiaofei Huang, Shuangjun Liu, Michael Wan, Nihang Fu, David Li Pino, Bharath R. Modayur, Sarah Ostadabbas
Appearance-Independent Pose-Based Posture Classification in Infants. ICPR Workshops (1) (2022)
Lai Wei, Nihang Fu, Yuqi Song, Qian Wang, Jianjun Hu
Probabilistic Generative Transformer Language models for Generative Design of Molecules. CoRR (2022)
Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
Materials Transformers Language Models for Generative Materials Design: a benchmark study. CoRR (2022)
Sadman Sadeed Omee, Steph-Yves M. Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu
Scalable deeper graph neural networks for high-performance materials property prediction. CoRR (2021)
Daniel Gleaves, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Nihang Fu, Jianjun Hu
Semi-supervised teacher-student deep neural network for materials discovery. CoRR (2021)
Xiaofei Huang, Nihang Fu, Shuangjun Liu, Sarah Ostadabbas
Invariant Representation Learning for Infant Pose Estimation with Small Data. FG (2021)
Shuangjun Liu, Xiaofei Huang, Nihang Fu, Sarah Ostadabbas
Heuristic Weakly Supervised 3D Human Pose Estimation in Novel Contexts without Any 3D Pose Ground Truth. CoRR (2021)
Xiaofei Huang, Nihang Fu, Sarah Ostadabbas
Infant Pose Learning with Small Data. CoRR (2020)
Shuangjun Liu, Xiaofei Huang, Nihang Fu, Cheng Li, Zhongnan Su, Sarah Ostadabbas
Simultaneously-Collected Multimodal Lying Pose Dataset: Towards In-Bed Human Pose Monitoring under Adverse Vision Conditions. CoRR (2020)