Abstract: Inhomogeneous linear ordinary differential equations (ODEs) and systems of ODEs can be solved in a variety of ways. However, hardware circuits that can perform the efficient analog ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Population balance equation (PBE) models have the potential to automate many ...
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
Abstract: Monte Carlo method was a new numerical method different from traditional method. It was based on probability and statistics theory, so it was also called as random sampling or statistical ...
Differential equations (DE) are mathematical equations that describe how a quantity changes as a function of one or several (independent) variables, often time or space. Differential equations play an ...
Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...
In many mechanistic medical, biological, physical, and engineered spatiotemporal dynamic models the numerical solution of partial differential equations (PDEs), especially for diffusion, fluid flow ...
When the chemical division of SCG needed to solve a complex manufacturing problem, its leaders made a bold choice: collaborate with Microsoft and use artificial intelligence to supplement its own ...
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