4 papers
MORPH: PDE Foundation Models with Arbitrary Data Modality
Mahindra Singh Rautela, Alexander Most, Siddharth Mansingh +6
We introduce MORPH, a modality-agnostic, autoregressive foundation model for partial differential equations (PDEs). MORPH is built on a convolutional vision transformer backbone th…
A Foundation Model for Material Fracture Prediction
Agnese Marcato, Aleksandra Pachalieva, Ryley G. Hill +14
Accurately predicting when and how materials fail is critical to designing safe, reliable structures, mechanical systems, and engineered components that operate under stress. Yet,…
VizGenie: Toward Self-Refining, Domain-Aware Workflows for Next-Generation Scientific Visualization
Ayan Biswas, Terece L. Turton, Nishath Rajiv Ranasinghe +7
We present VizGenie, a self-improving, agentic framework that advances scientific visualization through large language model (LLM) by orchestrating of a collection of domain-specif…
Volume Encoding Gaussians: Transfer Function-Agnostic 3D Gaussians for Volume Rendering
Landon Dyken, Andres Sewell, Will Usher +3
Visualizing the large-scale datasets output by HPC resources presents a difficult challenge, as the memory and compute power required become prohibitively expensive for end user sy…