Publications related to Quantile regression

Counting using deep learning regression gives value to ecological surveys

Devis Tuia, Benjamin Alexander Kellenberger

Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, whi ...

2021

On Modeling Glottal Source Information for Phonation Assessment in Parkinson's Disease

Mathew Magimai Doss, Julian David Fritsch

Parkinson's disease produces several motor symptoms, including different speech impairments that are known as hypokinetic dysarthria. Symptoms associated to dysarthria affect different dimensions of speech such as phonation, articulation, prosody, and inte ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

On the assessment of arterial compliance from carotid pressure waveform

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia, Stamatia Zoi Pagoulatou, Patrick Segers

In a progressively aging population, it is of utmost importance to develop reliable, noninvasive, and cost-effective tools to estimate biomarkers that can be indicative of cardiovascular risk. Various pathophysiological conditions are associated to changes ...

AMER PHYSIOLOGICAL SOC2021

Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion

Sylvain Calinon, Teguh Santoso Lembono

In this paper, we propose a framework to build a memory of motion for warm-starting an optimal control solver for the locomotion task of a humanoid robot. We use HPP Loco3D, a versatile locomotion planner, to generate offline a set of dynamically consisten ...

2020

Better Generic Objects Counting When Asking Questions to Images: A Multitask approach for Remote Sensing Visual Question Answering

Devis Tuia, Benjamin Alexander Kellenberger, Sylvain Lobry

Visual Question Answering for Remote Sensing (RSVQA) aims at extracting information from remote sensing images through queries formulated in natural language. Since the answer to the query is also provided in natural language, the system is accessible to n ...

2020

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Jan Sickmann Hesthaven, Mariella Kast, Mengwu Guo

We propose a non-intrusive reduced basis (RB) method for parametrized nonlinear partial differential equations (PDEs) that leverages models of different accuracy. From a collection of low-fidelity (LF) snapshots, parameter locations are extracted for the e ...

ELSEVIER SCIENCE SA2020

Online Robust Regression via SGD on the l1 loss

Nicolas Henri Bernard Flammarion, Scott William Pesme

We consider the robust linear regression problem in the online setting where we have access to the data in a streaming manner, one data point after the other. More specifically, for a true parameter , we consider the corrupted Gaussian linear model $ y=\la ...

2020

Bayesian regression explains how human participants handle parameter uncertainty

Michael Herzog, Jean-Pascal Théodor Pfister, Maya Anna Jastrzebowska, Mattew Pachai

Author summary How do humans make prediction when the critical factor that influences the quality of the prediction is hidden? Here, we address this question by conducting a simple psychophysical experiment in which participants had to extrapolate a parabo ...

2020

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Quantile regression

Counting using deep learning regression gives value to ecological surveys

On Modeling Glottal Source Information for Phonation Assessment in Parkinson's Disease

On the assessment of arterial compliance from carotid pressure waveform

Learning Optimal Impedance Control During Complex 3D Arm Movements

Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion

Better Generic Objects Counting When Asking Questions to Images: A Multitask approach for Remote Sensing Visual Question Answering

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Online Robust Regression via SGD on the l1 loss

Bayesian regression explains how human participants handle parameter uncertainty

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms

Graph Chatbot

Chat with Graph Search

Counting using deep learning regression gives value to ecological surveys

On Modeling Glottal Source Information for Phonation Assessment in Parkinson's Disease

Better Generic Objects Counting When Asking Questions to Images: A Multitask approach for Remote Sensing Visual Question Answering

On the assessment of arterial compliance from carotid pressure waveform

Learning Optimal Impedance Control During Complex 3D Arm Movements

Learning How to Walk: Warm-starting Optimal Control Solver with Memory of Motion

Online Robust Regression via SGD on the l1 loss

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Bayesian regression explains how human participants handle parameter uncertainty

Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms