4 papers
Online Optimization with Unknown Time-Varying Parameters from Noisy Gradient Measurements
Shivanshu Tripathi, Maziar Raissi
We study online optimization problems in which the cost function depends on latent, time-varying parameters that are unmeasurable and governed by unknown dynamics. Specifically, we…
Learning Parameterized Nonlinear Elasticity on Curved Surfaces
Yankang Liu, Ke Zhang, Maziar Raissi +1
We learn parameterized nonlinear elasticity on curved surfaces using a physics-informed neural network that enforces governing equations and boundary conditions directly through th…
ELPINN: Eulerian Lagrangian Physics-Informed Neural Network
Sukirt Thakur, Maziar Raissi
Physics-Informed Neural Networks (PINNs) have gained widespread popularity for solving inverse and forward problems across a range of scientific and engineering domains. However, m…
MixDiff: Mixing Natural and Synthetic Images for Robust Self-Supervised Representations
Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni +1
This paper introduces MixDiff, a new self-supervised learning (SSL) pre-training framework that combines real and synthetic images. Unlike traditional SSL methods that predominantl…