Videos

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Uncertainty Quantification and Hypocoercivity Based Sensitivity Analysis for Multiscale Kinetic Equations with Random Inputs Thumbnail

Uncertainty Quantification and Hypocoercivity Based Sensitivity Analysis for Multiscale Kinetic Equations with Random Inputs

Presenter
  • Shi Jin
November 15, 2017
IPAM
Automorphic forms and motivic cohomology I Thumbnail

Automorphic forms and motivic cohomology I

Presenter
  • Akshay Venkatesh
November 14, 2017
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II

Presenter
  • Russell Impagliazzo
November 14, 2017
IAS
Robust MCMC Sampling with Non-Gaussian and Hierarchical Priors Thumbnail

Robust MCMC Sampling with Non-Gaussian and Hierarchical Priors

Presenter
  • Matt Dunlop
November 14, 2017
IPAM
On matrix-valued log-concave functions Thumbnail

On matrix-valued log-concave functions

Presenter
  • Dario Cordero-Erausquin
November 14, 2017
SLMath
Billiards and Caustics Thumbnail

Billiards and Caustics

Presenter
  • Shiri Artstein
November 14, 2017
SLMath
Uncertainty Quantification and Thermodynamic Formalism for Stochastic Systems Thumbnail

Uncertainty Quantification and Thermodynamic Formalism for Stochastic Systems

Presenter
  • Luc Rey-Bellet
November 14, 2017
IPAM
Subgaussian and lacunary uniformly bounded orthonormal systems Thumbnail

Subgaussian and lacunary uniformly bounded orthonormal systems

Presenter
  • Gilles Pisier
November 14, 2017
SLMath
Refinements of Gaussian concentration for norms Thumbnail

Refinements of Gaussian concentration for norms

Presenter
  • Grigoris Paouris
November 14, 2017
SLMath
Decomposition theorem for semisimple algebraic holonomic D-modules Thumbnail

Decomposition theorem for semisimple algebraic holonomic D-modules

Presenter
  • Takuro Mochizuki
November 13, 2017
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I

Presenter
  • Russell Impagliazzo
November 13, 2017
IAS
Rigidity of the 3D hierarchical Coulomb gas Thumbnail

Rigidity of the 3D hierarchical Coulomb gas

Presenter
  • Sourav Chatterjee
November 13, 2017
SLMath