Abstract: Partial differential equations (PDEs) provide an accurate representation of mathematical and physical relationships in many modern engineering applications. In this paper, we utilize the ...
In this work, we frame PDE solving as tool invocation via LLM-driven agents and introduce PDE-Agent, the first toolchain-augmented multiagent collaboration framework, inheriting the reasoning capacity ...
The researchers’ device applies principles of neural networking to an optical framework. As a wave encoded with a PDE passes through the ONE’s series of components, its properties gradually shift and ...
Partial differential equations (PDEs) are workhorses of science and engineering. They describe a vast range of phenomena, from flow around a ship’s hull, to acoustics in a concert hall, to heat ...
Securities.io maintains rigorous editorial standards and may receive compensation from reviewed links. We are not a registered investment adviser and this is not investment advice. Please view our ...
Machine Learning ML offers significant potential for accelerating the solution of partial differential equations (PDEs), a critical area in computational physics. The aim is to generate accurate PDE ...
Abstract: Meshfree and particle methods are widely used in computational studies of partial differential equations, offering many advantages compared to traditional mesh- or grid-based numerical ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results