Publications associées à Bayesian adaptation of chaos representations using variational inference and sampling on geodesics

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

Bayesian adaptation of chaos representations using variational inference and sampling on geodesics

Graph Chatbot

Chattez avec Graph Search

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Multivariate geometric anisotropic Cox processes

Generalized parallel tempering on Bayesian inverse problems

Variational Inference with Mixture Model Approximation for Applications in Robotics

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Expectation propagation in the large data limit

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties

Expectation propagation in the large data limit

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Multivariate geometric anisotropic Cox processes

Generalized parallel tempering on Bayesian inverse problems

Variational Inference with Mixture Model Approximation for Applications in Robotics

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension