Videos

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Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems and optimal experimental design Thumbnail

Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems and optimal experimental design

Presenter
  • Omar Ghattas
October 7, 2020
IMSI
A probabilistic Takens theorem Thumbnail

A probabilistic Takens theorem

Presenter
  • Yonatan Gutman
May 16, 2019
IAS

Topology and Geometry for Vehicle-tracking Systems

Presenter
  • Paul Bendich
May 21, 2018
MBI
RNA Structure Characterization from High-Throughput Chemical Mapping Experiments Thumbnail

RNA Structure Characterization from High-Throughput Chemical Mapping Experiments

Presenter
  • Sharon Aviran
February 13, 2012
IMA
Counting and sampling minimum cuts in weighted planar graphs Thumbnail

Counting and sampling minimum cuts in weighted planar graphs

Presenter
  • Ivona Bezáková
January 13, 2012
SLMath
Team 4: Diffraction by photomasks Thumbnail

Team 4: Diffraction by photomasks

Presenter
  • Apo Sezginer
August 3, 2011
IMA

The conserved L5 loop establishes the pre-powerstroke conformation of the kinesin-5 motor, Eg5

Presenter
  • Sarah Rice
April 12, 2010
MBI