activity
20202024
most citedClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation

19 citations · 32 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2024★ 1 cited

Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming

Yongquan Qu, Mohamed Aziz Bhouri, Pierre Gentine

Accurate representations of unknown and sub-grid physical processes through parameterizations (or closure) in numerical simulations with quantified uncertainty are critical for res…

physics.ao-ph2024★ 2 cited

Stress-testing the coupled behavior of hybrid physics-machine learning climate simulations on an unseen, warmer climate

Jerry Lin, Mohamed Aziz Bhouri, Tom Beucler +2

Accurate and computationally-viable representations of clouds and turbulence are a long-standing challenge for climate model development. Traditional parameterizations that crudely…

cs.LG2023★ 2 cited

Multi-fidelity climate model parameterization for better generalization and extrapolation

Mohamed Aziz Bhouri, Liran Peng, Michael S. Pritchard +1

Machine-learning-based parameterizations (i.e. representation of sub-grid processes) of global climate models or turbulent simulations have recently been proposed as a powerful alt…

cs.LG2023★ 19 cited

ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation

Sungduk Yu, Zeyuan Hu, Akshay Subramaniam +44

Modern climate projections lack adequate spatial and temporal resolution due to computational constraints, leading to inaccuracies in representing critical processes like thunderst…

cs.LG2023

Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks

Mohamed Aziz Bhouri, Michael Joly, Robert Yu +2

Several fundamental problems in science and engineering consist of global optimization tasks involving unknown high-dimensional (black-box) functions that map a set of controllable…

stat.ML2022★ 3 cited

History-Based, Bayesian, Closure for Stochastic Parameterization: Application to Lorenz '96

Mohamed Aziz Bhouri, Pierre Gentine

Physical parameterizations are used as representations of unresolved subgrid processes within weather and global climate models or coarse-scale turbulent models, whose resolutions…