Three-dimensional convolutional neural network (3D-CNN) for heterogeneous material homogenization. - Chengping Rao; Yang Liu 130 (CoRR, 2020)

Physics-informed deep learning for incompressible laminar flows. - Chengping Rao; Hao Sun 002; Yang Liu 130 (CoRR, 2020)

Physics informed deep learning for computational elastodynamics without labeled data. - Chengping Rao; Hao Sun 002; Yang Liu 130 (CoRR, 2020)

Hard Encoding of Physics for Learning Spatiotemporal Dynamics. - Chengping Rao; Hao Sun 002; Yang Liu 130 (CoRR, 2021)

Embedding Physics to Learn Spatiotemporal Dynamics from Sparse Data. - Chengping Rao; Hao Sun 002; Yang Liu 130 (CoRR, 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)

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)

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

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)

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)