Google's DeepMind uncovered surprising solutions to the equations governing fluid dynamics, potentially accelerating vehicle ...

Tipping points in our climate predictions are both wildly dramatic and wildly uncertain. Can mathematicians make them useful?

An expert’s journey to implementing best process control via instrumentation, control strategies and PID control ...

This repo is the official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network" by Longxiang Jiang, Liyuan Wang, Xinkun Chu, Yonghao Xiao, and Hao Zhang ...

This course is available on the BSc in Mathematics and Economics, BSc in Mathematics with Data Science, BSc in Mathematics with Economics, BSc in Mathematics, Statistics and Business, Erasmus ...

Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...

Several fundamental results on the existence and behavior of solutions to semilinear functional differential equations are developed in a Banach space setting. The ideas are applied to ...

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...

Discover Clear Channel Outdoor's 2025 growth strategy—digitization, AI, and U.S. focus—driving revenue, innovation, and deleveraging.

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 ...