Videos

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Elicitability Thumbnail

Elicitability

Presenter
  • Christopher Chambers
May 4, 2022
IMSI
Evaluating Replicability: Considerations for Analyses and Implications for Design Thumbnail

Evaluating Replicability: Considerations for Analyses and Implications for Design

Presenter
  • Jacob Schauer
March 7, 2022
SLMath
Methods for scalable probabilistic inference Thumbnail

Methods for scalable probabilistic inference

Presenter
  • Dan Foreman-Mackey
November 17, 2021
IPAM
Computational/Statistical Gaps for Learning Neural Networks Thumbnail

Computational/Statistical Gaps for Learning Neural Networks

Presenter
  • Adam Klivans
April 13, 2021
IMSI
Approximation and learning with tree tensor networks Thumbnail

Approximation and learning with tree tensor networks

Presenter
  • Anthony Nouy
March 30, 2021
IPAM
On the statistical complexity of reinforcement learning Thumbnail

On the statistical complexity of reinforcement learning

Presenter
  • Mengdi Wang
February 24, 2020
IPAM
Constraint Satisfaction Problems and Probabilistic Combinatorics II Thumbnail

Constraint Satisfaction Problems and Probabilistic Combinatorics II

Presenter
  • Fotios Illiopoulos
November 26, 2019
IAS
High-dimensional cost landscape and gradient descent in Tensor PCA and its generalisations Thumbnail

High-dimensional cost landscape and gradient descent in Tensor PCA and its generalisations

Presenter
  • Chiara Cammarota
November 19, 2019
IPAM
Constraint Satisfaction Problems and Probabilistic Combinatorics I Thumbnail

Constraint Satisfaction Problems and Probabilistic Combinatorics I

Presenter
  • Fotios Illiopoulos
November 19, 2019
IAS
Machine learning for atomic and molecular simulations Thumbnail

Machine learning for atomic and molecular simulations

Presenter
  • Michele Ceriotti
November 18, 2019
IPAM
Machine learning for molecular simulations: priors and predictive constraints Thumbnail

Machine learning for molecular simulations: priors and predictive constraints

Presenter
  • Tristan Bereau
October 18, 2019
IPAM
Geometrical Approaches in Statistical Learning for the Construction of Digital Models of the Human Brain Thumbnail

Geometrical Approaches in Statistical Learning for the Construction of Digital Models of the Human Brain

Presenter
  • Stanley Durrleman
April 17, 2019
IPAM