New Trends in Scientific Computing - IPAM

New Trends in Scientific Computing

April 20 - 22, 2022

Schedule

All times in this Schedule are Pacific Time (PT)

Wednesday, April 20, 2022

Morning Session

08:00-08:50
Check-In/Light Breakfast (Hosted by IPAM)
08:50-09:00
Welcome & Opening Remarks: Dean Miguel García-Garibay (Dean of Physical Sciences, UCLA) and Dima Shlyakhtenko (Director, IPAM)
Session Chair: Frederic Gibou (University of California, Santa Barbara)
09:00-09:25
Bjorn Engquist (University of Texas at Austin)
Global convergence of stochastic gradient descent
09:30-09:55
Yann Brenier (Centre National de la Recherche Scientifique (CNRS))
Virtual Talk: From the Monge transportation problem to Einstein's gravitation through Euler's Hydrodynamics
10:00-10:15
Break
10:15-10:40
Chi-Wang Shu (Brown University)
Shock capturing methods for CFD: a review of Osher's contributions
10:45-11:10
Tom Goldstein (University of Maryland)
Title not available
11:15-11:30
Break
11:30-11:55
Hongkai Zhao (Duke University)
How much can one learn a PDE from its solution data

Afternoon Session

12:00-14:00
Lunch (on your own)
Session Chair: Andrea Bertozzi (University of California, Los Angeles )
14:00-14:25
Thomas Hou (California Institute of Technology)
Potentially singular behavior of 3D incompressible Euler equations and Navier-Stokes equations
14:30-14:55
Wuchen Li (University of South Carolina)
Controlling regularized conservation laws via entropy-entropy flux
15:00-15:30
Break
15:30-15:55
Chiu-Yen Kao (Claremont McKenna College)
Title not available
16:00-16:25
Lightning Poster Presentations (90 seconds each)
16:30-18:00
Poster Session & Reception (Hosted by IPAM)

Thursday, April 21, 2022

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
Session Chair: Chi-Wang Shu (Brown University)
09:00-09:25
Eli Yablonovitch (University of California, Berkeley (UC Berkeley))
Physics Does Digital Optimization—which we call Onsager Computing— for Machine Learning, Control Theory, Backpropagation, etc.
09:30-09:55
Andrea Bertozzi (University of California, Los Angeles (UCLA))
The MBO scheme on graphs for semi-supervised and unsupervised machine learning
10:00-10:15
Break
10:15-10:40
Ron Fedkiw (Stanford University)
Title not available
10:45-11:10
Wilfrid Gangbo (University of California, Los Angeles (UCLA))
Finite dimensional approximations of Hamilton-Jacobi-Bellman equations in spaces of probability measures
11:15-11:30
Break
11:30-11:55
Inwon Kim (University of California, Los Angeles (UCLA))
“MBO scheme with Wasserstein distance”

Afternoon Session

12:00-14:00
Lunch (on your own)
Session Chair: Wotao Yin (University of California, Los Angeles)
14:00-14:25
Guillermo Sapiro (Duke University)
Scientific computing for real health challenges
14:30-14:55
Frederic Gibou (University of California, Santa Barbara (UCSB))
Level-set methods and some recent development - a tribute to Stan Osher
15:00-15:30
Break
15:30-15:55
Russel Caflisch (New York University)
An Adjoint Method for the Nonlinear Boltzmann Equation
16:00-16:25
Rongjie Lai (Purdue University)
Learning Manifold-structured Data via Geometry Inspired DNNs
16:45-17:15
Group Photo
17:30-20:30
Banquet at the Faculty Center

Friday, April 22, 2022

Morning Session

08:00-09:00
Check-In/Breakfast (Hosted by IPAM)
Session Chair: Chi-Wang Shu (Brown University)
09:00-09:25
Lawrence (Craig) Evans (University of California, Berkeley (UC Berkeley))
Compensated compactness and 3-webs
09:30-09:55
Myungjoo Kang (Seoul National University)
Recent Developments of solving PDE using Neural Networks
10:00-10:15
Break
10:15-10:40
Barry Merriman (Roswell Biotechnologies)
From Motion by Mean Curvature to PDEs on Point Clouds: 30 Years of BMO[sher]
10:45-11:10
Fariba Fahroo (Air Force Office of Scientific Research (AFOSR))
Virtual Talk:
11:15-11:30
Break
11:30-11:55
Richard Tsai (University of Texas at Austin)
Side-effects of Learning from Low Dimensional Data Embedded in an Euclidean Space

Afternoon Session

12:00-12:05
Concluding Remarks
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