Application of the Kano-Hamilton Multiangle Inversion Method in Clear Atmospheres

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard H & ouml;gbom CLEAN algorithm widely used in radio astronomy to ...

We propose a local, non -intrusive model order reduction technique to accurately approximate the solution of coupled multi -component parametrized systems governed by partial differential equations. Our approach is based on the approximation of the boundar ...

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

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 ...

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 ...

Correlated errors of experimental data are a common but often neglected problem in physical sciences. Various tools are provided here for thorough propagation of uncertainties in cases of correlated errors. Discussed are techniques especially applicable to ...

Background: A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic netw ...

In this study, we examine the potential of several self-supervised deep learning models in predicting forest attributes and detecting forest changes using ESA Sentinel-1 and Sentinel-2 images. The performance of the proposed deep learning models is compare ...

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

Two related methods for inverting line-integrated measurements are presented in this research paper in the context of the recent deuterium-tritium experiments in the JET tokamak. Unlike traditional methods of tomography, these methods rely on making use of ...

This research aimed to evaluate the clinical features and computed tomography (CT) scans associated with poor outcomes in COVID-19 patients with acute kidney injury (AKI). A total of 351 COVID-19 patients (100 AKI, 251 non-AKI) hospitalized at Imam Hossein ...

Biomass resources can play an important role in the energy transition, being a dynamic feedstock that can be transformed either into solid, liquid or gaseous fuels. The biomass gasification is a versatile way to convert wastes into energy. In this work, th ...

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 ...

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) ...

In this second part of the development of a mechanistic kinetic model of the solar inactivation of E. coli enhanced with hydrogen peroxide, we evaluate the mechanisms based on photonic inactivation and integrate them into the kinetic model of the dark proc ...

Torque teno virus (TTV) is considered to be an ubiquitous member of the commensal human blood virome commonly reported in mixed genotype co-infections. This study investigates the genomic diversity of TTV in blood samples from 816 febrile Tanzanian childre ...

Application of the Kano-Hamilton Multiangle Inversion Method in Clear Atmospheres

Chattez avec Graph Search

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Iterative removal of sources to model the turbulent electromotive force

Model reduction of coupled systems based on non-intrusive approximations of the boundary response maps

On distributional autoregression and iterated transportation

Random matrix methods for high-dimensional machine learning models

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Reliable data-driven decision-making through optimal transport

Distributional Regression and Autoregression via Optimal Transport

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

Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Regressive Tomography and Direct Regressive Reconstruction: A Research Note

Roles of Clinical Features and Chest CT in Predicting the Outcomes of Hospitalized Patients with COVID-19 Developing AKI

Comparison of regression techniques for generating surrogate models to predict the thermodynamic behavior of biomass gasification systems

Minimax rate for optimal transport regression between distributions

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 2: Shine on you, crazy peroxide

Genomic Diversity of Torque Teno Virus in Blood Samples from Febrile Paediatric Outpatients in Tanzania: A Descriptive Cohort Study