Publications associées à Fonction gaussienne

Distributed Lossy Computation with Structured Codes: From Discrete to Continuous Sources

Michael Christoph Gastpar, Sung Hoon Lim, Adriano Pastore, Chen Feng

This paper considers the problem of distributed lossy compression where the goal is to recover one or more linear combinations of the sources at the decoder, subject to distortion constraints. For certain configurations, it is known that codes with algebra ...

2023

Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning

Colin Neil Jones, Yingzhao Lian, Loris Di Natale, Jicheng Shi, Emilio Maddalena

This manuscript offers the perspective of experimentalists on a number of modern data-driven techniques: model predictive control relying on Gaussian processes, adaptive data-driven control based on behavioral theory, and deep reinforcement learning. These ...

2023

A new variable shape parameter strategy for RBF approximation using neural networks

Jan Sickmann Hesthaven

The choice of the shape parameter highly effects the behaviour of radial basis function (RBF) approximations, as it needs to be selected to balance between the ill-conditioning of the interpolation matrix and high accuracy. In this paper, we demonstrate ho ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink, Tianfu Li

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

The Gray-Wyner Network and Wyner's Common Information for Gaussian Sources

Michael Christoph Gastpar, Erixhen Sula

This paper presents explicit solutions for two related non-convex information extremization problems due to Gray and Wyner in the Gaussian case. The first problem is the Gray-Wyner network subject to a sum-rate constraint on the two private links. Here, ou ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Sabine Süsstrunk, Majed El Helou, Kaan Okumus

Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

2022

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Xingchen Yang

Simultaneous prediction of wrist and hand motions is essential for the natural interaction with hand prostheses. In this paper, we propose a novel multi-out Gaussian process (MOGP) model and a multi-task deep learning (MTDL) algorithm to achieve simultaneo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

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Fonction gaussienne

Distributed Lossy Computation with Structured Codes: From Discrete to Continuous Sources

Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning

A new variable shape parameter strategy for RBF approximation using neural networks

Robust discrete choice models with t-distributed kernel errors

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Primordial black hole isocurvature modes from non-Gaussianity

The Gray-Wyner Network and Wyner's Common Information for Gaussian Sources

Local Nondeterminism and Local Times of the Stochastic Wave Equation Driven by Fractional-Colored Noise

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

Graph Chatbot

Chattez avec Graph Search

Primordial black hole isocurvature modes from non-Gaussianity

Distributed Lossy Computation with Structured Codes: From Discrete to Continuous Sources

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

A new variable shape parameter strategy for RBF approximation using neural networks

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning

Robust discrete choice models with t-distributed kernel errors

The Gray-Wyner Network and Wyner's Common Information for Gaussian Sources

Local Nondeterminism and Local Times of the Stochastic Wave Equation Driven by Fractional-Colored Noise

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples