HAL Training: Robust Physics-Informed Neural Networks

Center for Artificial Intelligence Innovation at NCSA is organizing online training sessions throughout the Spring 2023 semester to help users to get started with deep learning projects on HAL. These sessions are designed for novice users to learn about the system and start building deep neural network models. To sign up for training, just request a HAL account prior to the training session and mention "spring training" when describing how the system will be used in your project. Trainings will take place every Wednesday during the fall semester from 3-5pm via Zoom. 

Training Link: https://go.ncsa.illinois.edu/CAIIHALTraining

February 22, 2023: Robust Physics-Informed Neural Networks - Avik Roy

Training Overview: 
Physics Informed Neural Networks (PINNs) have recently been found to be effective PDE solvers. This talk will focus on how traditional PINN architectures along with physics-inspired regularizers fail to retrieve the intended solution when training data is noisy and how this problem can be solved using Gaussian Process based smoothing techniques.

Sessions will be recorded and available on the CAII website after the training.