Concept

Errors-in-variables models

Related publications (31)

Observed coupling between air mass history, secondary growth of nucleation mode particles and aerosol pollution levels in Beijing

Atmospheric aerosols have significant effects on the climate and on human health. New particle formation (NPF) is globally an important source of aerosols but its relevance especially towards aerosol mass loadings in highly polluted regions is still contro ...

2022

Hiding in Plain Sight: The Issue of Hidden Variables

Yimon Aye

Here we discuss "hidden variables", which are typically introduced during an experiment as a consequence of the application of two independent variables together to create a stimulus. With increased sophistication in modern chemical biology tools and relat ...

AMER CHEMICAL SOC2022

Analysing the effects of residential mobility behaviours on the composition of personal network in Switzerland

Vincent Kaufmann, Guillaume Simon Joseph Drevon, Gil Viry

Individual life courses are marked by residential mobility often associated with family and workplace changes and therefore likely to be related to the types of personal relationships people develop and maintain. Evidence about the relationship between res ...

2021

Socioeconomically Disadvantaged Neighborhoods Face Increased Persistence of SARS-CoV-2 Clusters

Stéphane Joost, Idris Guessous, David Nicolas De Ridder

Objective: To investigate the association between socioeconomic deprivation and the persistence of SARS-CoV-2 clusters. ...

FRONTIERS MEDIA SA2021

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Giovanni De Micheli, Sandro Carrara, Francesca Criscuolo, Mandresy Ivan Ny Hanitra

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...

2021

Impact of quantum-chemical metrics on the machine learning prediction of electron density

Anne-Clémence Corminboeuf, Alberto Fabrizio, Ksenia Briling

Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain a proper balance between the black-box nature of ML frameworks and the physics ...

AMER INST PHYSICS2021

A Continuized View on Nesterov Acceleration

Nicolas Henri Bernard Flammarion, Raphaël Jean Berthier

We introduce the "continuized" Nesterov acceleration, a close variant of Nesterov acceleration whose variables are indexed by a continuous time parameter. The two variables continuously mix following a linear ordinary differential equation and take gradien ...

2021

Two mixed finite element formulations for the weak imposition of the Neumann boundary conditions for the Darcy flow

Erik Burman, Riccardo Puppi

We propose two different discrete formulations for the weak imposition of the Neumann boundary conditions of the Darcy flow. The Raviart-Thomas mixed finite element on both triangular and quadrilateral meshes is considered for both methods. One is a consis ...

Walter De Gruyter2021

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

Julia Schmale, Katherine Colby Leonard, Andrea Baccarini, Robin Lewis Modini, Sebastian Johannes Heinz-Josef Landwehr, Alireza Moallemi, Fernando Perez Cruz, Christel Sybille Hassler

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remai ...

2021

ON THE DESIGN AND OPTIMIZATION OF WIDE ANGLE DIFFRACTIVE OPTICAL ELEMENTS

Dong Cheon Kim

Diffractive optical elements (DOEs) which consist of microstructure surface relief permit the generation of the spatial distribution of light beams by using a single element. Due to their compact size, design flexibility, and mass productivity, they are us ...

EPFL2021

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

IOP Publishing2011