From the 1 of 8 linked papers with an AI index.
1 citations · 1 across the 2 of their papers we have counts for
8 papers
Kinetic Optimization of Magnetic Mirror Confinement: Beyond Classical Loss-Cone Theory
Lukas Einkemmer, Martin Guerra, Qin Li +1
The paper formulates magnetic mirror design as a PDE‑constrained optimization problem using a reduced multispecies drift‑kinetic‑Poisson model and shows that self‑consistent electr…
Regional climate risk assessment from climate models using probabilistic machine learning
Zhong Yi Wan, Ignacio Lopez-Gomez, Robert Carver +4
Effective climate risk assessment is hindered by the resolution gap between coarse global climate models and the fine-scale information needed for regional decisions. We introduce…
Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models
Borong Zhang, MartÃn Guerra, Qin Li +1
We present Wideband Back-Projection Diffusion, an end-to-end probabilistic framework for approximating the posterior distribution induced by the inverse scattering map from wideban…
Generative AI for fast and accurate statistical computation of fluids
Roberto Molinaro, Samuel Lanthaler, Bogdan RaoniÄ +9
We present a generative AI algorithm for addressing the pressing task of fast, accurate, and robust statistical computation of three-dimensional turbulent fluid flows. Our algorith…
A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data
Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez +4
Chaotic systems, such as turbulent flows, are ubiquitous in science and engineering. However, their study remains a challenge due to the large range scales, and the strong interact…
Dynamical-generative downscaling of climate model ensembles
Ignacio Lopez-Gomez, Zhong Yi Wan, Leonardo Zepeda-Núñez +3
Regional high-resolution climate projections are crucial for many applications, such as agriculture, hydrology, and natural hazard risk assessment. Dynamical downscaling, the state…