A physics-informed neural network framework to investigate nonlinear and heterogenous shrinkage of drying plant cells
This paper introduces a novel Physics-Informed Neural Network-based (PINN-based) multi-
domain computational framework to analyse nonlinear and heterogeneous morphological …
domain computational framework to analyse nonlinear and heterogeneous morphological …
Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights
This review examines the current state of research on microscale cellular changes during
the drying of plant-based food materials (PBFM), with particular emphasis on computational …
the drying of plant-based food materials (PBFM), with particular emphasis on computational …
Architectural Strategies for the optimization of Physics-Informed Neural Networks
Physics-informed neural networks (PINNs) offer a promising avenue for tackling both
forward and inverse problems in partial differential equations (PDEs) by incorporating deep …
forward and inverse problems in partial differential equations (PDEs) by incorporating deep …
Architectural Insights for efficient Physics-Informed Neural Network optimization
H Saratchandran, SF Chng, S Lucey - openreview.net
Physics-informed neural networks (PINNs) offer a promising avenue for tackling both
forward and inverse problems in partial differential equations (PDEs) by combining deep …
forward and inverse problems in partial differential equations (PDEs) by combining deep …