In a novel study, researchers from the Icahn School of Medicine at Mount Sinai introduced LoGoFunc, an advanced computational tool that predicts pathogenic gain- and loss-of-function variants ...

By minimizing this composite loss function, the neural network learns to approximate the solution to the PDE while adhering to the physical constraints. Solving the Black-Scholes Equation with PINNs ...

14, the unknown functions to optimize are w, h, h η, and the trial space (also known as the hypothesis space in machine learning) for all 3 functions can be any machine-learning models. In this work, ...

The physics-informed neural network (PINN) has drawn much attention as it can reduce training data size and eliminate the need for physics equation identification. This paper presents the ...