Nature-inspired computers are shockingly good at math

Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex ...

These Brain-Inspired Computers Are Shockingly Good at Math

New research shows that advances in technology could help make future supercomputers far more energy efficient. Neuromorphic computers are modeled after the structure of the human brain, and researche ...

Pioneering Scientist Behind Revolutionary Weight-Loss Drugs and Leading Mathematician Honored with 2026 King Faisal Prize

Professors Svetlana Mojsov and Carlos Kenig, among other eminent figures, were selected to win the 48th session of the prize.
Interesting Engineering on MSN

World’s first neuromorphic supercomputer nears reality with brain-inspired math

The world’s first neuromorphic supercomputer is moving closer to reality after researchers at Sandia National Laboratories ...
IEEE

Sequence-to-Sequence Stacked Gate Recurrent Unit Networks for Approximating the Forward Problem of Partial Differential Equations

Abstract: We proposed an optimisation algorithm based on the sequence-to-sequence (Seq2Seq) stacking of the gate recurrent unit (GRU) model to characterise and approximate the forward problem of ...
IEEE

Extension of the Partial Integral Equation Representation to GPDE Input–Output Systems

Abstract: Partial integral equation (PIE) representation of a partial differential equation (PDE) allows using computationally tractable algorithms for analysis, simulation, and optimal control.
GitHub

Variational Physic-informed Neural Operator (VINO) for Learning Partial Differential Equations

Solving partial differential equations (PDEs) is a required step in the simulation of natural and engineering systems. The associated computational costs significantly increase when exploring various ...