A Mixed-Method Approach for Rapid Modeling of the Virtual Scene Building. - Pu Ren; Wenjian Wang; Mingquan Zhou; Chongbin Xu (IGTA, 2014)

A Rapid Modeling Method for 3D Architectural Scene. - Pu Ren; Zhe Wang; Yachun Fan; Mingquan Zhou; Guoguang Du (CW, 2016)

Automatic planar shape segmentation from indoor point clouds. - Wuyang Shui; Jin Liu; Pu Ren; Steve Maddock; Mingquan Zhou (VRCAI, 2016)

Sketch-Based Modeling and Immersive Display Techniques for Indoor Crime Scene Presentation. - Pu Ren; Mingquan Zhou; Jin Liu; Yachun Fan; Wenshuo Zhao; Wuyang Shui (ICDF2C, 2017)

Rapid three-dimensional scene modeling by sketch retrieval and auto-arrangement. - Pu Ren; Yachun Fan; Mingquan Zhou; Zhe Wang; Guoguang Du; Lu Qian (Comput. Graph., 2017)

Manifold Ranking for Sketch-Based 3D Model Retrieval. - Lu Qian; Yachun Fan; Mingquan Zhou; Hua Luan; Pu Ren (Trans. Edutainment, 2017)

Text to 3D Model of Chinese Ancient Architecture. - Yan Wang; Pu Ren; Mingquan Zhou; Wuyang Shui; Pengbo Zhou (CW, 2018)

A Sketch-based Rapid Modeling Method for Crime Scene Presentation. - Pu Ren; Wuyang Shui; Jin Liu; Yachun Fan; Wenshuo Zhao; Mingquan Zhou (J. Digit. Forensics Secur. Law, 2018)

Data-Driven Modeling for Chinese Ancient Architecture. - Pu Ren; Yan Wang; Mingquan Zhou; Zhongke Wu; Pengbo Zhou; Juan Zhang (Presence Teleoperators Virtual Environ., 2018)

Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting. - Pu Ren; Xinyu Chen 002; Lijun Sun 001; Hao Sun 002 (CoRR, 2020)

A Brief Discussion on Design Education and Practice in the Hypermedia Era. - Pu Ren; Zhe Wang; Mingjun Yang (HCI (18), 2021)

PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs. - Pu Ren; Chengping Rao; Yang Liu 130; Jian-Xun Wang 001; Hao Sun 002 (CoRR, 2021)

Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning. - Chengping Rao; Pu Ren; Yang Liu 130; Hao Sun 002 (ICLR, 2022)

A Line-drawing Extraction Method for Traditional Ornament based on 3D Models. - Pu Ren; Mingjun Yang (ISCID, 2022)

Arbitrary Style Transfer with Semantic Content Enhancement. - Guoshuai Li; Bin Cheng; Luoyu Cheng; Chongbin Xu; Xiaomin Sun 003; Pu Ren; Yong Yang; Qian Chen (VRCAI, 2022)

Physics-informed Deep Super-resolution for Spatiotemporal Data. - Pu Ren; Chengping Rao; Yang Liu 130; Zihan Ma 002; Qi Wang; Jian-Xun Wang 001; Hao Sun 002 (CoRR, 2022)

SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain. - Pu Ren; Chengping Rao; Su Chen; Jian-sun Wang; Hao Sun 002; Yang Liu 130 (CoRR, 2022)

An Unsupervised Machine Learning Approach for Ground Motion Clustering and Selection. - R. Bailey Bond; Pu Ren; Jerome F. Hajjar; Hao Sun (CoRR, 2022)

Collaborative state estimation of lithium-ion battery based on multi-time scale low-pass filter forgetting factor recursive least squares - double extended Kalman filtering algorithm. - Tao Long; Shunli Wang 002; Wen Cao; Pu Ren; Mingfang He; Carlos Fernandez (Int. J. Circuit Theory Appl., 2022)

Physics-informed neural network for seismic wave inversion in layered semi-infinite domain. - Pu Ren; Chengping Rao; Hao Sun 002; Yang Liu (CoRR, 2023)

SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning. - Pu Ren; N. Benjamin Erichson; Shashank Subramanian; Omer San; Zarija Lukic; Michael W. Mahoney (CoRR, 2023)

Encoding physics to learn reaction-diffusion processes. - Chengping Rao; Pu Ren; Qi Wang; Oral Buyukozturk; Hao Sun 002; Yang Liu 130 (Nat. Mac. Intell., 2023)

PhySR: Physics-informed deep super-resolution for spatiotemporal data. - Pu Ren; Chengping Rao; Yang Liu 130; Zihan Ma 002; Qi Wang; Jian-Xun Wang 001; Hao Sun 002 (J. Comput. Phys., 2023)

Model Balancing Helps Low-data Training and Fine-tuning. - Zihang Liu; Yuanzhe Hu; Tianyu Pang; Yefan Zhou; Pu Ren; Yaoqing Yang (EMNLP, 2024)

Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs. - Ilan Naiman; N. Benjamin Erichson; Pu Ren; Michael W. Mahoney; Omri Azencot (ICLR, 2024)

Application of Touch-based Interaction in Pattern Exhibition Narrative Display. - Luying Li; Pu Ren; Chunhui Zheng; Haiying Tao; Zhe Wang (ISCID, 2024)

Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning. - Wuyang Chen 001; Jialin Song; Pu Ren; Shashank Subramanian; Dmitriy Morozov; Michael W. Mahoney (NeurIPS, 2024)

P2C2Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics. - Qi Wang; Pu Ren; Hao Zhou; Xin-Yang Liu; Zhiwen Deng; Yi Zhang; Zeruizhi Cheng; Hongsheng Liu 002; Zidong Wang 010; Jian-Xun Wang 001; Ji-Rong Wen; Hao Sun 002; et al. (NeurIPS, 2024)

Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures. - R. Bailey Bond; Pu Ren; Jerome F. Hajjar; Hao Sun (CoRR, 2024)

Reasoning-Enhanced Object-Centric Learning for Videos. - Jian Li; Pu Ren; Yang Liu; Hao Sun 002 (CoRR, 2024)

WaveCastNet: An AI-enabled Wavefield Forecasting Framework for Earthquake Early Warning. - Dongwei Lyu; Rie Nakata; Pu Ren; Michael W. Mahoney; Arben Pitarka; Nori Nakata; N. Benjamin Erichson (CoRR, 2024)

Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling. - Pu Ren; Rie Nakata; Maxime Lacour; Ilan Naiman; Nori Nakata; Jialin Song; Zhengfa Bi; Osman Asif Malik; Dmitriy Morozov; Omri Azencot; N. Benjamin Erichson; Michael W. Mahoney (CoRR, 2024)

P2C2Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics. - Qi Wang; Pu Ren; Hao Zhou; Xin-Yang Liu; Zhiwen Deng; Yi Zhang; Ruizhi Chengze; Hongsheng Liu 002; Zidong Wang 010; Jian-Xun Wang 001; Ji-Rong Wen; Hao Sun 002; et al. (CoRR, 2024)

SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain. - Pu Ren; Chengping Rao; Su Chen; Jian-Xun Wang 001; Hao Sun 002; Yang Liu 130 (Comput. Phys. Commun., 2024)

Reasoning-Enhanced Object-Centric Learning for Videos. - Jian Li; Pu Ren; Yang Liu 130; Hao Sun 002 (KDD (1), 2025)

Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction. - Yuan Mi; Pu Ren; Hongteng Xu; Hongsheng Liu 002; Zidong Wang 010; Yike Guo; Ji-Rong Wen; Hao Sun 002; Yang Liu 005 (KDD (1), 2025)

Learning spatiotemporal dynamics from sparse data via a high-order physics-encoded network. - Pu Ren; Jialin Song; Chengping Rao; Qi Wang; Yike Guo; Hao Sun 002; Yang Liu 005 (Comput. Phys. Commun., 2025)