PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple
Operators for Forecasting Fluid Dynamics

PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics

15 September 2024

Jingmin Sun

Zecheng Zhang

Hayden Schaeffer

Papers citing "PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics"

5 / 5 papers shown

Title
Cauchy Random Features for Operator Learning in Sobolev Space Chunyang Liao Deanna Needell Hayden Schaeffer 31 0 0 01 Mar 2025
A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions Elisa Negrini Yuxuan Liu Liu Yang Stanley Osher Hayden Schaeffer AI4CE 81 0 0 09 Feb 2025
Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study Hao Liu Zecheng Zhang Wenjing Liao Hayden Schaeffer 16 1 0 01 Oct 2024
Time-Series Forecasting, Knowledge Distillation, and Refinement within a Multimodal PDE Foundation Model Derek Jollie Jingmin Sun Zecheng Zhang Hayden Schaeffer AI4TS 18 1 0 17 Sep 2024
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 229 74,467 0 18 May 2015