papers

Publications (28)

physics.comp-ph2020

Learned discretizations for passive scalar advection in a 2-D turbulent flow

Jiawei Zhuang, Dmitrii Kochkov, Yohai Bar-Sinai +2

The computational cost of fluid simulations increases rapidly with grid resolution. This has given a hard limit on the ability of simulations to accurately resolve small scale feat…

cond-mat.dis-nn2019

Learning data driven discretizations for partial differential equations

Yohai Bar-Sinai, Stephan Hoyer, Jason Hickey +1

The numerical solution of partial differential equations (PDEs) is challenging because of the need to resolve spatiotemporal features over wide length and timescales. Often, it is…

physics.optics2019

Freeform Diffractive Metagrating Design Based on Generative Adversarial Networks

Jiaqi Jiang, David Sell, Stephan Hoyer +3

A key challenge in metasurface design is the development of algorithms that can effectively and efficiently produce high performance devices. Design methods based on iterative opti…

cs.LG2019

Inundation Modeling in Data Scarce Regions

Zvika Ben-Haim, Vladimir Anisimov, Aaron Yonas +4

Flood forecasts are crucial for effective individual and governmental protective action. The vast majority of flood-related casualties occur in developing countries, where providin…

physics.ao-ph2026

AIMIP Phase 1: systematic evaluations of AI weather and climate models

Brian Henn, Christopher S. Bretherton, Nikolay Koldunov +18

The paper introduces AIMIP Phase 1, an intercomparison framework for AI‑based weather and climate models that evaluates their ability to simulate historical atmospheric conditions…

#ai weather models#model intercomparison#reanalysis training#el niño response
cs.LG2025

Accelerating scientific discovery with the common task framework

J. Nathan Kutz, Peter Battaglia, Michael Brenner +12

Machine learning (ML) and artificial intelligence (AI) algorithms are transforming and empowering the characterization and control of dynamic systems in the engineering, physical,…