Publications related to Heat demand estimation for different building types at regional scale considering building parameters and urban topography

Distributional Regression and Autoregression via Optimal Transport

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Streamlining the regionalization of economy-wide material flow accounts (EW-MFA): The case of swiss cantons

Claudia Rebeca Binder Signer, Aristide Henri Roger Athanassiadis, Nicole Sophie Wiedmann

Current levels of resource use and pollution emissions are responsible for the trespassing of most planetary boundaries. As such, operational and contextual analysis is needed to provide mitigation strategies and policies. This article aims to streamline E ...

ELSEVIER2023

Distribution-on-distribution regression via optimal transport maps

Victor Panaretos, Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...

OXFORD UNIV PRESS2022

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - part 1: The dark side of peroxide

César Pulgarin, Stefanos Giannakis, Ling Feng

The present bi-partite work describes the development and validation of a mechanistic kinetic model of SODIS E. coli inactivation, enhanced with H2O2. In this first part, the mechanism of the baseline dark phenomena is modelled. A mechanistic model involvi ...

ELSEVIER SCIENCE SA2022

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Nikolaos Geroliminis, Emmanouil Barmpounakis

The work proposes a multi-modal regional mean speed regression analysis for the city network of Athens, Greece. The dataset from pNUEMA experiment is used in the present context. Accumulations and mean speeds of different modes are estimated and compared t ...

2021

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Silvestro Micera, Vincent Alexandre Mendez, Leonardo Pollina, Fiorenzo Artoni

The control of robotic prosthetic hands (RPHs) for upper limb amputees is far from optimal. Simultaneous and proportional finger control of a RPH based on EMG signals is still challenging. Based on EMG and kinematics recordings of subjects following a pre- ...

IEEE2021

Gaussian Process Regression for Materials and Molecules

Michele Ceriotti, David Mark Wilkins

We provide an introduction to Gaussian process regression (GPR) machinelearning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of in ...

AMER CHEMICAL SOC2021

Physics-Inspired Structural Representations for Molecules and Materials

Michele Ceriotti, Félix Benedito Clément Musil, Andrea Grisafi

The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic-scale structure of matter and its properties, involves transforming the Cartesian coordinates of the atom ...

AMER CHEMICAL SOC2021

Heat demand estimation for different building types at regional scale considering building parameters and urban topography

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Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Streamlining the regionalization of economy-wide material flow accounts (EW-MFA): The case of swiss cantons

Distribution-on-distribution regression via optimal transport maps

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - part 1: The dark side of peroxide

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Gaussian Process Regression for Materials and Molecules

Physics-Inspired Structural Representations for Molecules and Materials

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Distributional Regression and Autoregression via Optimal Transport

Distribution-on-distribution regression via optimal transport maps

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Streamlining the regionalization of economy-wide material flow accounts (EW-MFA): The case of swiss cantons

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Deep Learning with Convolutional Neural Network for Proportional Control of Finger Movements from surface EMG Recordings

Mechanistic modelling of solar disinfection (SODIS) kinetics of Escherichia coli, enhanced with H2O2 - part 1: The dark side of peroxide

Physics-Inspired Structural Representations for Molecules and Materials

Gaussian Process Regression for Materials and Molecules