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 ...

The idea that we’re living inside a simulation, as popularized by “The Matrix” franchise, has piqued the interest of scientists for decades. In 2003, philosopher Nick Bostrom proposed in a highly ...

A neural network is a machine learning model originally inspired by how the human brain works (Courtesy: Shutterstock/Jackie Niam) Precision measurements of theoretical parameters are a core element ...

Abstract: This letter presents a novel inverse design method for metasurface antennas (MSAs). Specifically, we propose a data generation strategy by employing a Voronoi-based partitioning algorithm, ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

Learn how forward propagation works in neural networks using Python! This tutorial explains the process of passing inputs through layers, calculating activations, and preparing data for ...

Forbes contributors publish independent expert analyses and insights. I am an MIT Senior Fellow & Lecturer, 5x-founder & VC investing in AI AI is big and powerful – many humans with even a passing ...

Please be aware that this is a beta release. Beta means that the product may not be functionally or feature complete. At this early phase the product is not yet expected to fully meet the quality, ...

1 Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands 2 Department of Chemical Engineering and Chemistry, Eindhoven University of Technology, Eindhoven, ...

With increasing model complexity, models are typically re-used and evolved rather than starting from scratch. There is also a growing challenge in ensuring that these models can seamlessly work across ...