From the 1 of 3 linked papers with an AI index.
3 papers
LIGO-PINN: Learned Initialization via Gated Optimization to Alleviate Convergence Failures in Physics Informed Neural Networks
Nilay Anurag, Shital Adhikari, Taniya Kapoor +1
The paper introduces LIGO-PINN, a learned weight initialization method using gated layerwise optimization to improve the training stability and convergence of physics-informed neur…
TRIE: An Evaluation Framework for Stochastic PDE Surrogates
Bharat Srikishan, Javier E. Santos, Nikhil Muralidhar +1
Many scientific systems exhibit uncertainty from stochastic forcing, unresolved degrees of freedom, or imperfect observations, making reliable surrogate forecasting fundamentally d…
Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
Bharat Srikishan, Daniel O'Malley, Mohamed Mehana +2
Modeling the evolution of physical systems is critical to many applications in science and engineering. As the evolution of these systems is governed by partial differential equati…