Based on deep neural network, elliptic partial differential equations in complex regions are solved. Accurate and effective strategies and numerical methods for elliptic partial differential equations ...

Many problems in science and engineering can be mathematically modeled using partial differential equations (PDEs), which are essential for fields like computational fluid dynamics (CFD), molecular ...

A research team has developed a novel direct sampling method based on deep generative models. Their method enables efficient ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

A mathematician at Carnegie Mellon University has developed an easier way to solve quadratic equations. The mathematician hopes this method will help students avoid memorizing obtuse formulas.

Deep Learning for Partial Differential Equations. Contribute to NNDam/DeepLearningPDE development by creating an account on GitHub.

By using PyTorch — a popular open-source AI library — Dr. Betgeri was able to implement automatic differentiation, allowing ...

Solving High Dimensional Partial Differential Equations with Deep Neural Networks - pooyasf/DGM ...

PINNs therefore represent a key solution for mathematical modeling based on first principles, enabling both the solution of differential equations (forward problem) and the identification of model ...