10 citations · 18 across the 7 of their papers we have counts for
8 papers
Nodal discontinuous Galerkin methods for non-ideal equations of state: pressure equilibrium preservation and entropy correction
Jesse CHan, Hendrik Ranocha, Raymond Park +3
Structure-preserving discontinuous Galerkin (DG) methods typically improve the robustness of high order simulations of real fluids. In addition to conservation, key structures incl…
An AI agent for treatment reasoning over a biomedical tool universe
Shanghua Gao, Ayush Noori, Richard Zhu +13
Treatment reasoning underpins every therapeutic decision, integrating disease context, comorbidities, medications, contraindications, and evolving biomedical knowledge to select an…
Beyond the summation-by-parts property: nullspace consistency, sparsity, and regularization for FSBP operators
Jan Glaubitz, Armin Iske, Joshua Lampert +1
We investigate the construction and performance of summation-by-parts (SBP) operators, which offer a powerful framework for the systematic development of structure-preserving numer…
Towards provable energy-stable overset grid methods using sub-cell summation-by-parts operators
Jan Glaubitz, Joshua Lampert, Andrew R. Winters +1
Overset grid methods handle complex geometries by overlapping simpler, geometry-fitted grids to cover the original, more complex domain. However, ensuring their stability---particu…
Structure-Preserving Numerical Methods for Fokker-Planck Equations
Hanna Bartel, Joshua Lampert, Hendrik Ranocha
A common way to numerically solve Fokker-Planck equations is the Chang-Cooper method in space combined with one of the Euler methods in time. However, the explicit Euler method is…
Structure-Preserving Numerical Methods for Two Nonlinear Systems of Dispersive Wave Equations
Joshua Lampert, Hendrik Ranocha
We use the general framework of summation-by-parts operators to construct conservative, energy-stable, and well-balanced semidiscretizations of two different nonlinear systems of d…
Natural Language Programming in Medicine: Administering Evidence Based Clinical Workflows with Autonomous Agents Powered by Generative Large Language Models
Akhil Vaid, Joshua Lampert, Juhee Lee +26
Generative Large Language Models (LLMs) hold significant promise in healthcare, demonstrating capabilities such as passing medical licensing exams and providing clinical knowledge.…
HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes
Akhil Vaid, Joy Jiang, Ashwin Sawant +9
The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer learning…