Publications associées à What is the Fourier Transform of a Spatial Point Process?

Publications associées (12)

A Deep Learning Model for Chemical Shieldings in Molecular Organic Solids Including Anisotropy

Florian Mathieu Pascal Viscosi, Ruben Rodriguez Madrid, David Lyndon Emsley, Michele Ceriotti, Matthias Linus Kellner, Jacob Brian Holmes, Yuxuan Zhang

Nuclear Magnetic Resonance (NMR) chemical shifts are powerful probes of local atomic and electronic structure that can be used to resolve the structures of powdered or amorphous molecular solids. Chemical shift driven structure elucidation depends critical ...

AMER CHEMICAL SOC2025

Analytical and EZmock covariance validation for the DESI 2024 results

Jiaxi Yu, Daniel Felipe Forero Sanchez

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full-Shape two approaches are usually considered. First: anal ...

2025

Detection of the Geminga pulsar at energies down to 20 GeV with the LST-1 of CTAO

Andrii Neronov, Volodymyr Savchenko, Oleg Kalashev

Context. Geminga is the third gamma-ray pulsar firmly detected by imaging atmospheric Cherenkov telescopes (IACTs) after the Crab and the Vela pulsars. Most of its emission is expected at tens of giga-electronvolts, and, out of the planned telescopes of th ...

2025

Tractably modelling dependence in networks beyond exchangeability

Sofia Charlotta Olhede

We propose a general framework for modelling network data that is designed to describe aspects of non-exchangeability, with an explicit parameter describing the degree of non-exchangeability. Conditional on latent (unobserved) variables, the edges of the n ...

2025

Resampling estimation of discrete choice models

Michel Bierlaire, Matthieu Marie Cochon de Lapparent, Nicola Marco Ortelli

In the context of discrete choice modeling, the extraction of potential behavioral insights from large datasets is often limited by the poor scalability of maximum likelihood estimation. This paper proposes a simple and fast dataset-reduction method that i ...

2024

Social Learning with Adaptive Models

Ali H. Sayed, Virginia Bordignon

In social learning, a network of agents assigns probability scores (beliefs) to some hypotheses of interest, based on the observation of streaming data. First, each agent updates locally its belief with the information extracted from the current data throu ...

IEEE2024

DESI mock challenge: constructing DESI galaxy catalogues based on FastPM simulations

Jean-Paul Richard Kneib, Cheng Zhao, Andrei Variu

Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large-scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one must build real ...

Oxford Univ Press2023

LHC Schottky Spectrum from Macro-Particle Simulations

Tatiana Pieloni, Nicolas Frank Mounet, Christophe Emmanuel R. Lannoy

We introduce a method for building Schottky spectra from macro-particle simulations performed with the PyHEADTAIL code, applied to LHC beam conditions. In this case, the use of a standard Fast Fourier Transform (FFT) algorithm to recover the spectral conte ...

JACoW Publishing2022

Euclid: Covariance of weak lensing pseudo-C-l estimates Calculation, comparison to simulations, and dependence on survey geometry

Georges Meylan

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-C-l estimates of tomographic cosmic shear power spectra. Using two existing publicly av ...

EDP SCIENCES S A2022

Bridging the gap between model-driven and data-driven methods in the era of Big Data

Gael Lederrey

Data-driven and model-driven methodologies can be regarded as competitive fields since they tackle similar problems such as prediction. However, these two fields can learn from each other to improve themselves. Indeed, data-driven methodologies have been d ...

EPFL2022

Experimental assessment of traffic density estimation at link and network level with sparse data

Nikolaos Geroliminis

This paper investigates the accuracy of mean density estimation from direct sensing at link and network levels. Different calculation methods are compared depending on sensor type, probe vehicles or loop detectors, and availability to quantify the magnitud ...

TAYLOR & FRANCIS LTD2022

Is There a Cap on Longevity? A Statistical Review

Anthony Christopher Davison, Léo Raymond-Belzile

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security sys ...

ANNUAL REVIEWS2022