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New particle formation event detection with Mask R-CNN

Publications associées (37)

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Data and code associated with the paper 'Mode-Specific Coupling of Nanoparticle-on-Mirror Cavities with Cylindrical Vector Beams'

Christophe Marcel Georges Galland, Valeria Vento, Sachin Suresh Verlekar, Philippe Andreas Rölli

Data and code associated with the following paper: V. Vento et al, Nano Lett. 2023 A thorough explanation of the experiment performed is available there. The name of each sub-folder and file in Maps_data_code.zip indicates the correspondin ...

EPFL Infoscience2023

ALMOST SURE SCATTERING OF THE ENERGY-CRITICAL NLS IN d > 6

Katie Sabrina Catherine Rosie Marsden

We study the energy-critical nonlinear Schrodinger equation with randomised initial data in dimensions d > 6. We prove that the Cauchy problem is almost surely globally well-posed with scattering for randomised supercritical initial data in H-s(Rd) wheneve ...

Springfield2023

This upload contains the relevant scripts, notebooks, and datasets to reproduce the numerically obtained results of the Journal article "Three-dimensional buoyant hydraulic fractures: finite volume release" by Möri and Lecampion, (2023). ...

EPFL Infoscience2023

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Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

ELSEVIER2022

Data and Workflow to: Three-dimensional buoyant hydraulic fracture growth: constant release from a point source (Möri and Lecampion, (2022))

Brice Tanguy Alphonse Lecampion, Andreas Möri

This upload contains the relevant scripts, notebooks, and datasets to reproduce the numerically obtained results of the Journal article "Three-dimensional buoyant hydraulic fracture growth: constant release from a point source" by Möri and Lecampion, (2022 ...

2022

A logconcave likelihood is as important to proper statistical inference as a convex cost function is important to variational optimization. Quantization is often disregarded when writing likelihood models, ignoring the limitations of the physical detectors ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

I did not use WeChat as my main method or main source of materials, but I realized that during my fieldwork in China, I did use WeChat very often to help me collect data, and I see the potential of using WeChat as an increasingly important method for furth ...

2022

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This document corresponds to the appendix of the paper Regionalisation in high share renewable energy system modelling by Schnidrig et al. in redaction, and is based on the Master thesis of Amara Slaymaker 2021, giving additional information about the meth ...

2021

Sparsely observed functional time series: estimation and prediction

Victor Panaretos, Tomas Rubin

Functional time series analysis, whether based on time or frequency domain methodology, has traditionally been carried out under the assumption of complete observation of the constituent series of curves, assumed stationary. Nevertheless, as is often the c ...

INST MATHEMATICAL STATISTICS2020

Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows

Nicola Marzari, Giovanni Pizzi, Martin Uhrin, Sebastiaan Philippe Huber

Over the last two decades, the field of computational science has seen a dramatic shift towards incorporating high-throughput computation and big-data analysis as fundamental pillars of the scientific discovery process. This has necessitated the developmen ...

2020