Videos

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Three principles of data science: predictability, stability, and computability

Presenter
  • Bin Yu
September 14, 2016
IMA

Object Oriented Data Analysis

Presenter
  • J. S. Marron
September 12, 2016
MBI

Topological analysis of biological data using persistence landscapes

Presenter
  • Peter Bubenik
September 12, 2016
MBI

From Computer and Data back to Topology and Geometry

Presenter
  • Dan Burghelea
May 19, 2016
MBI

Excision and product results for persistent homology

Presenter
  • Gunnar Carlsson
May 16, 2016
MBI
Making Sense of Data: the Human Side of Data Analysis Thumbnail

Making Sense of Data: the Human Side of Data Analysis

Presenter
  • Danyel Fisher
April 12, 2016
IPAM
Big Image Data. An art-historical Perspective Thumbnail

Big Image Data. An art-historical Perspective

Presenter
  • Harald Klinke
March 24, 2016
IPAM
Balanced POD Model Reduction for PDE Systems Thumbnail

Balanced POD Model Reduction for PDE Systems

Presenter
  • John Singler
March 16, 2016
IMA
Visual Exploration of Image Data Thumbnail

Visual Exploration of Image Data

Presenter
  • Damon Crockett
March 15, 2016
IPAM
Should You Derive or Let the Data Drive? Towards a Hybrid Physics-based Data-driven Symbiosis Thumbnail

Should You Derive or Let the Data Drive? Towards a Hybrid Physics-based Data-driven Symbiosis

Presenter
  • Lior Horesh
February 22, 2016
IMA
Memory networks for unstructured data Thumbnail

Memory networks for unstructured data

Presenter
  • Arthur Szlam
February 10, 2016
IPAM
Deep learning on geometric data with intrinsic convolutional neural networks Thumbnail

Deep learning on geometric data with intrinsic convolutional neural networks

Presenter
  • Michael Bronstein
February 9, 2016
IPAM