Exploring Lagrangian Data Assimilation: Methods And Uncertainty With Nan Chen

Exploring Lagrangian Data Assimilation: Methods and Uncertainty with Nan Chen

Society for Industrial and Applied Mathematics (SIAM)

Looking into the Earth: Modelling, Inversion and Uncertainty Quantification in Computational...

PASC Conference

Assimilation of Lagrangian data - Chris Jones

International Centre for Theoretical Sciences

Data Assimilation – Basic Theory by Varahan

International Centre for Theoretical Sciences

Lagrangian Neural Network (LNN) [Physics Informed Machine Learning]

"Model Uncertainty Quantification for Data Assimilation in partially observed ..."　Sahani Pathiraja

計算科学eラーニングアーカイブチャンネル

Efficient Statistically Accurate Lagrangian Data Assimilation of Sea Ice Using Non-Interacting Floes

Nudging methods in geophysical data assimilation: Hands-on lab - Didier Auroux

International Centre for Theoretical Sciences

Impact studies with Data Assimilation using Nudging and 3DVAR - C.V. Srinivas

International Centre for Theoretical Sciences

Uncertainty-Penalized Bayesian Information Criterionfor Parametric PDE Discovery

Pongpisit Thanasutives

Quantifying uncertainty in deep learning – Arno Solin and Lassi Meronen

Aalto University

1W-MINDS: Jianfeng Cai, 03/11/2021, Landscape analysis of nonconvex optimization in phase retrieval

Nan Chen, A Fast Preconditioner and a Cheap Surrogate Model For Complex Nonlinear Systems

NCSU Mathematics

Tutorial

International Centre for Theoretical Sciences

Aleksandr Aravkin - Algorithms for Nonsmooth, Nonconvex Problems in Data-Driven Discovery

Physics Informed Machine Learning

Kathleen Champion - Data-driven discovery of coordinates and governing equations

Physics Informed Machine Learning

On the long-time behavior for a damped Navier-Stokes-Bardina model

MODEMAT Research Center for Mathematical Modeling