367 citations · 436 across the 18 of their papers we have counts for
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Neuroevolution of Physics-Informed Neural Nets: Benchmark Problems and Comparative Results
Nicholas Sung Wei Yong, Jian Cheng Wong, Pao-Hsiung Chiu +3
The potential of learned models for fundamental scientific research and discovery is drawing increasing attention worldwide. Physics-informed neural networks (PINNs), where the los…
Design of Turing Systems with Physics-Informed Neural Networks
Jordon Kho, Winston Koh, Jian Cheng Wong +2
Reaction-diffusion (Turing) systems are fundamental to the formation of spatial patterns in nature and engineering. These systems are governed by a set of non-linear partial differ…
Robustness of Physics-Informed Neural Networks to Noise in Sensor Data
Jian Cheng Wong, Pao-Hsiung Chiu, Chin Chun Ooi +1
Physics-Informed Neural Networks (PINNs) have been shown to be an effective way of incorporating physics-based domain knowledge into neural network models for many important real-w…