Nature

Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks

The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained ...
IEEE

A Novel Zeroing Neural Network for Time-Varying Matrix Pseudoinversion in the Presence of Linear Noises

Abstract: The computation of matrix pseudoinverses is a recurrent requirement across various scientific computing and engineering domains. The prevailing models for matrix pseudoinverse typically ...
C&EN

Molecular Simulations with a Pretrained Neural Network and Universal Pairwise Force Fields

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Machine Learning Force Fields (MLFFs) promise to enable general molecular simulations ...
C&EN

Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network

Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...
IEEE

Composite Learning Neural Network Tracking Control of Articulated Soft Robots

Abstract: Controlling articulated soft robots (ASRs) driven by variable stiffness actuators (VSAs) is challenging because they are highly nonlinear and difficult to model accurately. This paper ...
GitHub

Physics-Informed Neural Network (PINN) for Navier-Stokes Equations in MATLAB

This MATLAB implementation trains a Physics-Informed Neural Network (PINN) to solve the Navier-Stokes equations for incompressible fluid flow. The model is validated against the well-known Lid-Driven ...
GitHub

tutorial_pinn_to_solve_hde

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