Abstract: Physics-informed neural networks (PINNs) have great potential for flexibility and effectiveness in forward modeling and inversion of seismic waves. However, coordinate-based neural networks ...

Department of Materials Science and Engineering, Whiting School of Engineering, The Johns Hopkins University, Baltimore, Maryland 21218, United States Department of Electrical and Computer Engineering ...

Abstract: Rapid advancements of artificial neural networks for computer sciences, inspired by biological neuron interaction mechanisms, may be leveraged in reverse to synthetic biology by providing ...