4 papers
Physics-Informed Deep B-Spline Networks
Zhuoyuan Wang, Raffaele Romagnoli, Saviz Mowlavi +1
Physics-informed machine learning offers a promising framework for solving complex partial differential equations (PDEs) by integrating observational data with governing physical l…
Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data
Swati Rallapalli, Shannon Gallagher, Andrew O. Mellinger +6
We study the efficacy of fine-tuning Large Language Models (LLMs) for the specific task of report (government archives, news, intelligence reports) summarization. While this topic…
Building Hybrid B-Spline And Neural Network Operators
Raffaele Romagnoli, Jasmine Ratchford, Mark H. Klein
Control systems are indispensable for ensuring the safety of cyber-physical systems (CPS), spanning various domains such as automobiles, airplanes, and missiles. Safeguarding CPS n…
Deep operator learning-based surrogate models for aerothermodynamic analysis of AEDC hypersonic waverider
Khemraj Shukla, Jasmine Ratchford, Luis Bravo +4
Neural networks are universal approximators that traditionally have been used to learn a map between function inputs and outputs. However, recent research has demonstrated that dee…