Publications related to Performance of two model-free data interpretation methods for continuous monitoring of structures under environmental variations

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

Small area vulnerability, household food insecurity and child malnutrition in Medellin, Colombia: results from a repeated cross-sectional study

Stéphane Joost

Summary Background Malnutrition and food insecurity might be driven not only by individual factors but also by contextual conditions, such as area-level deprivation or vulnerability. This study aimed to analyze the association between area-level vulnerabil ...

2023

Neural controlled differential equations for crop classification

Accurate and scalable crop classification is important for food security and sustainable resources management. The temporal development of crops, i.e., their phenology, is a continuous phenomena that if properly captured, can help to discern them. The nove ...

2021

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

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

Juan Ramón Troncoso-Pastoriza

Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithm ...

2020

Fast Automatic Smoothing for Generalized Additive Models

Anthony Christopher Davison, Yousra El Bachir

Generalized additive models (GAMs) are regression models wherein parameters of probability distributions depend on input variables through a sum of smooth functions, whose degrees of smoothness are selected by L-2 regularization. Such models have become th ...

MICROTOME PUBL2019

Data-Interpretation Methodologies for Practical Asset-Management

Ian Smith, Yves Sylvain Gilles Reuland, Sai Ganesh Sarvotham Pai

Monitoring and interpreting structural response using structural-identification methodologies improves understanding of civil-infrastructure behavior. New sensing devices and inexpensive computation has made model-based data interpretation feasible in engi ...

2019

Data-driven reduced order modeling for time-dependent problems

Jan Sickmann Hesthaven, Mengwu Guo

A data-driven reduced basis (RB) method for parametrized time-dependent problems is proposed. This method requires the offline preparation of a database comprising the time history of the full-order solutions at parameter locations. Based on the full-order ...

2018

COLA: Decentralized Linear Learning

Martin Jaggi, Lie He

Decentralized machine learning is a promising emerging paradigm in view of global challenges of data ownership and privacy. We consider learning of linear classification and regression models, in the setting where the training data is decentralized over ma ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

A Practical Engineering Approach to Interpreting Measurement Data in Uncertain Contexts

Ian Smith, Sai Ganesh Sarvotham Pai

Measurement data interpretation has the potential to improve asset management through quantification of reserve capacity and execution of well-engineered interventions. Many recent proposals for data interpretation that include uncertainty are not appropri ...

ASCE2017

Performance of two model-free data interpretation methods for continuous monitoring of structures under environmental variations

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Distributional Regression and Autoregression via Optimal Transport

Small area vulnerability, household food insecurity and child malnutrition in Medellin, Colombia: results from a repeated cross-sectional study

Neural controlled differential equations for crop classification

Physics-Inspired Structural Representations for Molecules and Materials

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

Fast Automatic Smoothing for Generalized Additive Models

Data-Interpretation Methodologies for Practical Asset-Management

Data-driven reduced order modeling for time-dependent problems

COLA: Decentralized Linear Learning

A Practical Engineering Approach to Interpreting Measurement Data in Uncertain Contexts

Distributional Regression and Autoregression via Optimal Transport

Physics-Inspired Structural Representations for Molecules and Materials

Fast Automatic Smoothing for Generalized Additive Models

Data-driven reduced order modeling for time-dependent problems

COLA: Decentralized Linear Learning

A Practical Engineering Approach to Interpreting Measurement Data in Uncertain Contexts

Small area vulnerability, household food insecurity and child malnutrition in Medellin, Colombia: results from a repeated cross-sectional study

Neural controlled differential equations for crop classification

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

Data-Interpretation Methodologies for Practical Asset-Management