26 citations · 30 across the 5 of their papers we have counts for
5 papers
Learning Pore-scale Multiphase Flow from 4D Velocimetry
Chunyang Wang, Linqi Zhu, Yuxuan Gu +9
Multiphase flow in porous media underpins subsurface energy and environmental technologies, including geological CO storage and underground hydrogen storage, yet pore-scale dyn…
Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
Xuanchi Ren, Yifan Lu, Tianshi Cao +13
Collecting and annotating real-world data for safety-critical physical AI systems, such as Autonomous Vehicle (AV), is time-consuming and costly. It is especially challenging to ca…
Learning Distributions of Complex Fluid Simulations with Diffusion Graph Networks
Mario Lino, Tobias Pfaff, Nils Thuerey
Physical systems with complex unsteady dynamics, such as fluid flows, are often poorly represented by a single mean solution. For many practical applications, it is crucial to acce…
Imagen 3
Imagen-Team-Google, :, Jason Baldridge +257
We introduce Imagen 3, a latent diffusion model that generates high quality images from text prompts. We describe our quality and responsibility evaluations. Imagen 3 is preferred…
MultiScale MeshGraphNets
Meire Fortunato, Tobias Pfaff, Peter Wirnsberger +2
In recent years, there has been a growing interest in using machine learning to overcome the high cost of numerical simulation, with some learned models achieving impressive speed-…