An effective explicit pressure gradient scheme implemented in the two-level non-staggered grids for incompressible Navier-Stokes equations. - Pao-Hsiung Chiu; Tony W. H. Sheu; Reui-Kuo Lin (J. Comput. Phys., 2008)

A dispersion-relation-preserving algorithm for a nonlinear shallow-water wave equation. - Pao-Hsiung Chiu; Long Lee; Tony W. H. Sheu (J. Comput. Phys., 2009)

On the development of a dispersion-relation-preserving dual-compact upwind scheme for convection-diffusion equation. - Pao-Hsiung Chiu; Tony W. H. Sheu (J. Comput. Phys., 2009)

Development of a dispersively accurate conservative level set scheme for capturing interface in two-phase flows. - Tony W. H. Sheu; Ching-Hao Yu; Pao-Hsiung Chiu (J. Comput. Phys., 2009)

A sixth-order dual preserving algorithm for the Camassa-Holm equation. - Pao-Hsiung Chiu; Long Lee; Tony W. H. Sheu (J. Comput. Appl. Math., 2010)

Viscous and inviscid regularizations in a class of evolutionary partial differential equations. - Roberto Camassa; Pao-Hsiung Chiu; Long Lee; Tony W. H. Sheu (J. Comput. Phys., 2010)

A differentially interpolated direct forcing immersed boundary method for predicting incompressible Navier-Stokes equations in time-varying complex geometries. - Pao-Hsiung Chiu; Reui-Kuo Lin; Tony W. H. Sheu (J. Comput. Phys., 2010)

A conservative phase field method for solving incompressible two-phase flows. - Pao-Hsiung Chiu; Yan-Ting Lin (J. Comput. Phys., 2011)

On the development of a high-order compact scheme for exhibiting the switching and dissipative solution natures in the Camassa-Holm equation. - Tony W. H. Sheu; Pao-Hsiung Chiu; Ching-Hao Yu (J. Comput. Phys., 2011)

Milkcrown simulation using OpenACC accelerated framework. - Chih-Wen Chang; Chia-Chen Kuo; Pao-Hsiung Chiu (SIGGRAPH ASIA Posters, 2014)

A coupled phase field framework for solving incompressible two-phase flows. - Pao-Hsiung Chiu (J. Comput. Phys., 2019)

Improved Surrogate Modeling of Fluid Dynamics with Physics-Informed Neural Networks. - Jian Cheng Wong; Chinchun Ooi; Pao-Hsiung Chiu; My Ha Dao (CoRR, 2021)

U-Net-Based Surrogate Model For Evaluation of Microfluidic Channels. - Quang Tuyen Le; Pao-Hsiung Chiu; Chinchun Ooi (CoRR, 2021)

CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method. - Pao-Hsiung Chiu; Jian Cheng Wong; Chinchun Ooi; My Ha Dao; Yew-Soon Ong (CoRR, 2021)

Design of Turing Systems with Physics-Informed Neural Networks. - Jordon Kho; Winston Koh; Jian Cheng Wong; Pao-Hsiung Chiu; Chin Chun Ooi (SSCI, 2022)

Physics Compliance as a Metric for Neural Network Uncertainty. - Zhong Liang Ou Yang; Yang Jiang; Jian Cheng Wong; Pao-Hsiung Chiu; Weijiang Zhao; My Ha Dao; Chin Chun Ooi (SSCI, 2022)

Robustness of Physics-Informed Neural Networks to Noise in Sensor Data. - Jian Cheng Wong; Pao-Hsiung Chiu; Chinchun Ooi; My Ha Da (CoRR, 2022)

JAX-Accelerated Neuroevolution of Physics-informed Neural Networks: Benchmarks and Experimental Results. - Nicholas Wei Yong Sung; Jian Cheng Wong; Pao-Hsiung Chiu; Abhishek Gupta 001; Chinchun Ooi; Yew-Soon Ong (CoRR, 2022)

Neuroevolution of Physics-Informed Neural Nets: Benchmark Problems and Comparative Results. - Nicholas Sung; Jian Cheng Wong; Chin Chun Ooi; Abhishek Gupta 001; Pao-Hsiung Chiu; Yew-Soon Ong (GECCO Companion, 2023)

LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry. - Jian Cheng Wong; Pao-Hsiung Chiu; Chinchun Ooi; My Ha Dao; Yew-Soon Ong (IJCNN, 2023)

Generalizable Neural Physics Solvers by Baldwinian Evolution. - Jian Cheng Wong; Chin Chun Ooi; Abhishek Gupta 001; Pao-Hsiung Chiu; Joshua Shao Zheng Low; My Ha Dao; Yew-Soon Ong (CoRR, 2023)

cDFIB: A convolutional direct forcing immersed boundary method for solving incompressible flows with time-varying geometries. - Pao-Hsiung Chiu (J. Comput. Phys., 2023)

Importance of Nyquist-Shannon Sampling in Training of Physics-Informed Neural Networks. - Chin Chun Ooi; Anran Huang; Zhao Wei; Shiyao Qin; Jian Cheng Wong; Pao-Hsiung Chiu; My Ha Dao (IJCNN, 2024)

Physics-Informed Neuro-Evolution (PINE): A Survey and Prospects. - Jian Cheng Wong; Abhishek Gupta 001; Chin Chun Ooi; Pao-Hsiung Chiu; Jiao Liu; Yew-Soon Ong (CoRR, 2025)

Multi-level datasets training method in Physics-Informed Neural Networks. - Yao-Hsuan Tsai; Hsiao-Tung Juan; Pao-Hsiung Chiu; Chao-An Lin (CoRR, 2025)

Evolvable Conditional Diffusion. - Zhao Wei; Chin Chun Ooi; Abhishek Gupta 001; Jian Cheng Wong; Pao-Hsiung Chiu; Sheares Xue Wen Toh; Yew-Soon Ong (CoRR, 2025)