Nihang Fu

According to our database, Nihang Fu authored at least 17 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study.

Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong, Ming Hu, Jianjun Hu

CoRR, 2024

2023

Probabilistic generative transformer language models for generative design of molecules.

Lai Wei, Nihang Fu, Yuqi Song, Qian Wang, Jianjun Hu

J. Cheminformatics, December, 2023

Global Mapping of Structures and Properties of Crystal Materials.

Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Lai Wei, Jianjun Hu

J. Chem. Inf. Model., June, 2023

Material transformers: deep learning language models for generative materials design.

Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu

Mach. Learn. Sci. Technol., March, 2023

Simultaneously-Collected Multimodal Lying Pose Dataset: Enabling In-Bed Human Pose Monitoring.

Shuangjun Liu, Xiaofei Huang, Nihang Fu, Cheng Li, Zhongnan Su, Sarah Ostadabbas

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Generative Design of inorganic compounds using deep diffusion language models.

Rongzhi Dong, Nihang Fu, Dirisuriya M. D. Siriwardane, Jianjun Hu

CoRR, 2023

MD-HIT: Machine learning for materials property prediction with dataset redundancy control.

Qin Li, Nihang Fu, Sadman Sadeed Omee, Jianjun Hu

CoRR, 2023

2022

Scalable deeper graph neural networks for high-performance materials property prediction.

Sadman Sadeed Omee, Steph-Yves M. Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu

Patterns, 2022

Composition based oxidation state prediction of materials using deep learning.

Nihang Fu, Jeffrey Hu, Ying Feng, Gregory Morrison, Hans-Conrad zur Loye, Jianjun Hu

CoRR, 2022

Materials Transformers Language Models for Generative Materials Design: a benchmark study.

Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu

CoRR, 2022

Physics Guided Generative Adversarial Networks for Generations of Crystal Materials with Symmetry Constraints.

Yong Zhao, Edirisuriya M. Dilanga Siriwardane, Zhenyao Wu, Ming Hu, Nihang Fu, Jianjun Hu

CoRR, 2022

Appearance-Independent Pose-Based Posture Classification in Infants.

Xiaofei Huang, Shuangjun Liu, Michael Wan, Nihang Fu, David Li Pino, Bharath R. Modayur, Sarah Ostadabbas

Proceedings of the Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges, 2022

2021

Semi-supervised teacher-student deep neural network for materials discovery.

Daniel Gleaves, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Nihang Fu, Jianjun Hu

CoRR, 2021

Heuristic Weakly Supervised 3D Human Pose Estimation in Novel Contexts without Any 3D Pose Ground Truth.

Shuangjun Liu, Xiaofei Huang, Nihang Fu, Sarah Ostadabbas

CoRR, 2021

Invariant Representation Learning for Infant Pose Estimation with Small Data.

Xiaofei Huang, Nihang Fu, Shuangjun Liu, Sarah Ostadabbas

Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021

2020

Infant Pose Learning with Small Data.

Xiaofei Huang, Nihang Fu, Sarah Ostadabbas

CoRR, 2020

Simultaneously-Collected Multimodal Lying Pose Dataset: Towards In-Bed Human Pose Monitoring under Adverse Vision Conditions.

Shuangjun Liu, Xiaofei Huang, Nihang Fu, Cheng Li, Zhongnan Su, Sarah Ostadabbas

CoRR, 2020