Statistical and Computational Challenges in Probabilistic Scientific Machine Learning (SciML)

June 9 — 13, 2025

Description

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Scientific Machine Learning (SciML) holds immense promise in complementing and enhancing classical methods, thus facilitating scientific discovery and revolutionizing engineering practices. Particularly note-worthy is its probabilistic viewpoint, which offers novel strategies for comprehending and addressing challenges posed by model uncertainties in real-world applications. The workshop aims to serve as a platform for researchers across diverse scientific domains to exchange scientific and technical expertise in related topics. It provides an opportunity to confront statistical and computational challenges collectively while fostering communication channels to bridge the scientific computing and machine learning communities.

Funding

Priority funding consideration will be given to those to register by April 8, 2025. Funding is limited.

Organizers

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L D
Laurent Demanet Massachusetts Institute of Technology (MIT)
Q L
Qin Li University of Wisconsin-Madison
R W
Rebecca Willett University of Chicago
L Z
Leonardo Zepeda-Núñez Google and University of Wisconsin-Madison

Speakers

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R B
Ricardo Baptista Caltech
N B
Nicholas Boffi Carnegie Mellon University
J B
Joan Bruna Flatiron Institute
N C
Nisha Chandramoorthy University of Chicago
I D
Ivan Dokmanic Universität Basel
D G
Dimitrios Giannakis Dartmouth
J H
Jiequn Han Flatiron Institute
B H
Bamdad Hosseini University of Washington, Seattle
Y K
Yuehaw Khoo University of Chicago
N K
Nik Kovachki NVIDIA
G M
Gunnar Martinsson University of Texas, Austin
R M
Romit Maulik Penn State
N N
Nick Nusken King’s College London
A O
Assad Oberai University of Southern California
B P
Benjamin Peherstorfer New York University
A R
Andrej Risteski Carnegie Mellon University
F S
Fei Sha Google
R V
René Vidal University of Pennsylvania
H Y
Haizhao Yang University of Maryland
Y Y
Yunan Yang Cornell University
R Y
Rose Yu University of California, San Diego

Registration

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IMSI is committed to making all of our programs and events inclusive and accessible. Contact [email protected] to request disability-related accommodations.

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