YoVDO

Poseidon: Efficient Foundation Models for PDEs - Tutorial 1

Offered By: MICDE University of Michigan via YouTube

Tags

Partial Differential Equations Courses Machine Learning Courses Neural Networks Courses Fluid Dynamics Courses Scientific Computing Courses Numerical Methods Courses Finite Element Method Courses Computational Physics Courses Foundation Models Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore an in-depth tutorial on Poseidon, an efficient foundation model for Partial Differential Equations (PDEs), presented by Maximilian Herde. Delve into the intricacies of this innovative approach to solving complex mathematical problems in the field of computational science. Learn how Poseidon leverages advanced techniques to enhance the efficiency and accuracy of PDE solutions, potentially revolutionizing various scientific and engineering applications. Gain valuable insights into the underlying principles, implementation strategies, and practical applications of this cutting-edge model. Suitable for researchers, engineers, and students interested in computational mathematics and scientific computing.

Syllabus

Maximilian Herde: Poseidon: Efficient Foundation Models for PDEs (Tutorial 1)


Taught by

MICDE University of Michigan

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent