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)

Infant Pose Learning with Small Data. - Xiaofei Huang; Nihang Fu; Sarah Ostadabbas (CoRR, 2020)

Invariant Representation Learning for Infant Pose Estimation with Small Data. - Xiaofei Huang; Nihang Fu; Shuangjun Liu; Sarah Ostadabbas (FG, 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)

Semi-supervised teacher-student deep neural network for materials discovery. - Daniel Gleaves; Edirisuriya M. Dilanga Siriwardane; Yong Zhao 014; Nihang Fu; Jianjun Hu (CoRR, 2021)

Appearance-Independent Pose-Based Posture Classification in Infants. - Xiaofei Huang; Shuangjun Liu; Michael Wan; Nihang Fu; David Li Pino; Bharath R. Modayur; Sarah Ostadabbas (ICPR Workshops (1), 2022)

Physics Guided Generative Adversarial Networks for Generations of Crystal Materials with Symmetry Constraints. - Yong Zhao 014; Edirisuriya M. Dilanga Siriwardane; Zhenyao Wu; Ming Hu; Nihang Fu; Jianjun Hu (CoRR, 2022)

Materials Transformers Language Models for Generative Materials Design: a benchmark study. - Nihang Fu; Lai Wei 008; Yuqi Song; Qinyang Li; Rui Xin; Sadman Sadeed Omee; Rongzhi Dong; Edirisuriya M. Dilanga Siriwardane; Jianjun Hu (CoRR, 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)

Scalable deeper graph neural networks for high-performance materials property prediction. - Sadman Sadeed Omee; Steph-Yves M. Louis; Nihang Fu; Lai Wei 008; Sourin Dey; Rongzhi Dong; Qinyang Li; Jianjun Hu (Patterns, 2022)

MD-HIT: Machine learning for materials property prediction with dataset redundancy control. - Qin Li; Nihang Fu; Sadman Sadeed Omee; Jianjun Hu (CoRR, 2023)

Generative Design of inorganic compounds using deep diffusion language models. - Rongzhi Dong; Nihang Fu; Dirisuriya M. D. Siriwardane; Jianjun Hu (CoRR, 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)

Material transformers: deep learning language models for generative materials design. - Nihang Fu; Lai Wei 008; Yuqi Song; Qinyang Li; Rui Xin; Sadman Sadeed Omee; Rongzhi Dong; Edirisuriya M. Dilanga Siriwardane; Jianjun Hu (Mach. Learn. Sci. Technol., 2023)

Global Mapping of Structures and Properties of Crystal Materials. - Qinyang Li; Rongzhi Dong; Nihang Fu; Sadman Sadeed Omee; Lai Wei 008; Jianjun Hu (J. Chem. Inf. Model., 2023)

Probabilistic generative transformer language models for generative design of molecules. - Lai Wei 008; Nihang Fu; Yuqi Song; Qian Wang; Jianjun Hu (J. Cheminformatics, 2023)

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)