Pao-Hsiung Chiu

According to our database, Pao-Hsiung Chiu authored at least 35 papers between 2008 and 2026.

Collaborative distances:

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

2026

Transferable Physics-Informed Representations via Closed-Form Head Adaptation.

Jian Cheng Wong, Isaac Yin Chung Lai, Pao-Hsiung Chiu, Chin Chun Ooi, Abhishek Gupta, Yew-Soon Ong

CoRR, April, 2026

FFV-PINN: A Fast Physics-Informed Neural Network with Simplified Finite Volume Discretization and Residual Correction.

Chang Wei, Yuchen Fan, Jian Cheng Wong, Chin Chun Ooi, Heyang Wang, Pao-Hsiung Chiu

CoRR, March, 2026

Bridging Computational Fluid Dynamics Algorithm and Physics-Informed Learning: SIMPLE-PINN for Incompressible Navier-Stokes Equations.

Chang Wei, Yuchen Fan, Chin Chun Ooi, Jian Cheng Wong, Heyang Wang, Pao-Hsiung Chiu

CoRR, March, 2026

Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction.

Pao-Hsiung Chiu, Jian Cheng Wong, Chin Chun Ooi, Chang Wei, Yuchen Fan, Yew-Soon Ong

CoRR, February, 2026

PINEAPPLE: Physics-Informed Neuro-Evolution Algorithm for Prognostic Parameter Inference in Lithium-Ion Battery Electrodes.

Karkulali Pugalenthi, Jian Cheng Wong, Qizheng Yang, Pao-Hsiung Chiu, My Ha Dao, Nagarajan Raghavan, Chinchun Ooi

CoRR, February, 2026

Evolutionary Optimization of Physics-Informed Neural Networks: Evo-PINN Frontiers and Opportunities.

Jian Cheng Wong, Abhishek Gupta, Chin Chun Ooi, Pao-Hsiung Chiu, Jiao Liu, Yew-Soon Ong

IEEE Comput. Intell. Mag., February, 2026

Out-of-Distribution Generalization for Neural Physics Solvers.

Zhao Wei, Chin Chun Ooi, Jian Cheng Wong, Abhishek Gupta, Pao-Hsiung Chiu, Yew-Soon Ong

CoRR, January, 2026

Physics-Informed Uncertainty Enables Reliable AI-driven Design.

Tingkai Xue, Chin Chun Ooi, Yang Jiang, Pham Luu Trung Duong, Pao-Hsiung Chiu, Weijiang Zhao, Nagarajan Raghavan, My Ha Dao

CoRR, January, 2026

2025

Multi-level datasets training method in Physics-Informed Neural Networks.

Yao-Hsuan Tsai, Hsiao-Tung Juan, Pao-Hsiung Chiu, Chao-An Lin

CoRR, April, 2025

Physics-Informed Neuro-Evolution (PINE): A Survey and Prospects.

Jian Cheng Wong, Abhishek Gupta, Chin Chun Ooi, Pao-Hsiung Chiu, Jiao Liu, Yew-Soon Ong

CoRR, January, 2025

Evolvable Conditional Diffusion.

Zhao Wei, Chin Chun Ooi, Abhishek Gupta, Jian Cheng Wong, Pao-Hsiung Chiu, Sheares Xue Wen Toh, Yew-Soon Ong

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

2024

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

Proceedings of the International Joint Conference on Neural Networks, 2024

Soft Constraint in Local Structure Approximation-PINN.

Jian Cheng Wong, Pao-Hsiung Chiu, Chinchun Ooi, My Ha Dao

Proceedings of the IEEE Conference on Artificial Intelligence, 2024

2023

cDFIB: A convolutional direct forcing immersed boundary method for solving incompressible flows with time-varying geometries.

Pao-Hsiung Chiu

J. Comput. Phys., 2023

Generalizable Neural Physics Solvers by Baldwinian Evolution.

Jian Cheng Wong, Chin Chun Ooi, Abhishek Gupta, Pao-Hsiung Chiu, Joshua Shao Zheng Low, My Ha Dao, Yew-Soon Ong

CoRR, 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

Proceedings of the International Joint Conference on Neural Networks, 2023

Neuroevolution of Physics-Informed Neural Nets: Benchmark Problems and Comparative Results.

Nicholas Sung, Jian Cheng Wong, Chin Chun Ooi, Abhishek Gupta, Pao-Hsiung Chiu, Yew-Soon Ong

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

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, Chinchun Ooi, Yew-Soon Ong

CoRR, 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

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

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Design of Turing Systems with Physics-Informed Neural Networks.

Jordon Kho, Winston Koh, Jian Cheng Wong, Pao-Hsiung Chiu, Chin Chun Ooi

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

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

U-Net-Based Surrogate Model For Evaluation of Microfluidic Channels.

Quang Tuyen Le, Pao-Hsiung Chiu, Chinchun Ooi

CoRR, 2021

Improved Surrogate Modeling of Fluid Dynamics with Physics-Informed Neural Networks.

Jian Cheng Wong, Chinchun Ooi, Pao-Hsiung Chiu, My Ha Dao

CoRR, 2021

2019

A coupled phase field framework for solving incompressible two-phase flows.

Pao-Hsiung Chiu

J. Comput. Phys., 2019

2014

Milkcrown simulation using OpenACC accelerated framework.

Chih-Wen Chang, Chia-Chen Kuo, Pao-Hsiung Chiu

Proceedings of the SIGGRAPH Asia 2014 Posters, Shenzhen, China, December 3-6, 2014, 2014

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

A conservative phase field method for solving incompressible two-phase flows.

Pao-Hsiung Chiu, Yan-Ting Lin

J. Comput. Phys., 2011

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

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 sixth-order dual preserving algorithm for the Camassa-Holm equation.

Pao-Hsiung Chiu, Long Lee, Tony W. H. Sheu

J. Comput. Appl. Math., 2010

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

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

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

2008

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