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Estimation of Conditional Distributions using Gaussian Mixture Models

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The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Fei Pu

In this thesis, we study systems of linear and/or non-linear stochastic heat equations and fractional heat equations in spatial dimension

1

driven by space-time white noise. The main topic is the study of hitting probabilities for the solutions to these ...

EPFL2018

Estimation of Conditional Distributions using Gaussian Mixture Models

Graph Chatbot

Chattez avec Graph Search

Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions

Geometrically-Conditioned Point Diffusion Models

A Wasserstein-based measure of conditional dependence

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures

Learning Constrained Distributions of Robot Configurations with Generative Adversarial Network

Distributionally Robust Optimization with Polynomial Densities: Theory, Models and Algorithms

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Wasserstein Distributionally Robust Learning

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Multi-Modal Mean-Fields via Cardinality-Based Clamping

Wasserstein Distributionally Robust Learning

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Geometrically-Conditioned Point Diffusion Models

A Wasserstein-based measure of conditional dependence

Learning Constrained Distributions of Robot Configurations with Generative Adversarial Network

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Distributionally Robust Optimization with Polynomial Densities: Theory, Models and Algorithms

Multi-Modal Mean-Fields via Cardinality-Based Clamping

Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures