Penn Engineers have developed a new way to use AI to solve inverse partial differential equations (PDEs), a particularly ...

Zoe Brown, a mathematics graduate student from London, Ky., is the 2025-26 recipient of WKU’s John D. Minton Award.

Understanding the Transmission LandscapeLiver flukes, particularly Clonorchis sinensis and Opisthorchis species, represent a significant yet often ...

Differential equations don’t have to feel like an endless maze of formulas. With the right mix of tech tools, real-world context, and problem-solving strategies, they can become a skill you actually ...

We are pleased to announce that the article "Isomonodromy Deformations at an Irregular Singularity with Coalescing Eigenvalues", published in 2019 in Duke Mathematical Journal, has received the 2026 ...

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...

This course provides an introduction to topics involving ordinary differential equations. Emphasis is placed on the development of abstract concepts and applications for first-order and linear ...

Note: The article usage is presented with a three- to four-day delay and will update daily once available. Due to ths delay, usage data will not appear immediately following publication. Citation ...

Abstract: Neural Ordinary Differential Equations (NODEs) revolutionize the way we view residual networks as solvers for initial value problems (IVPs), with layer depth serving as the time step. In ...

ABSTRACT: An entirely new framework is established for developing various single- and multi-step formulations for the numerical integration of ordinary differential equations. Besides polynomials, ...