Concept

Quantile regression

Related publications (68)

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

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EPFL2023

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Olga Fink, Luca Biggio

On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an essential layer of safety assurance that could lead to more principled decision making by enabling sound risk assessment and management. The safety and reliability impr ...

2023

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

Olga Fink, Ismail Nejjar

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep feature encoder by minimizing the discrepa ...

IEEE2023

How are cells instructed to form somite boundaries by the zebrafish segmentation clock?

Olivier François Venzin

In vertebrate embryos, the elongating body axis is patterned via the sequential and rhyth-mic production of segments from a posterior unsegmented tissue called the presomitic mesoderm (PSM). This process is controlled by a population of cellular oscillator ...

EPFL2023

Minimax rate for optimal transport regression between distributions

Victor Panaretos, Laya Ghodrati

Distribution-on-distribution regression considers the problem of formulating and es-timating a regression relationship where both covariate and response are probability distributions. The optimal transport distributional regression model postulates that th ...

ELSEVIER2022

Mesh d-refinement: a data-based computational framework to account for complex material response

Jean-François Molinari, Antonio Joaquin Garcia Suarez, Sacha Zenon Wattel

Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an abstract phase space in ...

2022

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

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

Smart Armband with Graphene Textile Electrodes for EMG-based Muscle Fatigue Monitoring

Ata Jedari Golparvar

We report the successful acquisition of surface electromyography (sEMG) signals from an intelligent armband and its application in localized muscle fatigue monitoring with a costume-designed, small-scale front-end readout circuitry. The correlation coeffic ...

IEEE2021

Postmortem memory of public figures in news and social media

Robert West

Deceased public figures are often said to live on in collective memory. We quantify this phenomenon by tracking mentions of 2,362 public figures in English-language online news and social media (Twitter) 1 y before and after death. We measure the sharp spi ...

NATL ACAD SCIENCES2021

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