Francisco Villaescusa-Navarro

Francisco Villaescusa-Navarro

Princeton University

H-index: 45

North America-United States

About Francisco Villaescusa-Navarro

Francisco Villaescusa-Navarro, With an exceptional h-index of 45 and a recent h-index of 41 (since 2020), a distinguished researcher at Princeton University, specializes in the field of Astrophysics, cosmology, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Atomic hydrogen shows its true colours: Correlations between HI and galaxy colour in simulations

Improving astrophysical scaling relations with machine learning

Cosmological baryon spread and impact on matter clustering in CAMELS

Debiasing with Diffusion: Probabilistic reconstruction of Dark Matter fields from galaxies with CAMELS

Zooming by in the CARPoolGP lane: new CAMELS-TNG simulations of zoomed-in massive halos

Probing the Circum-Galactic Medium with Fast Radio Bursts: Insights from the CAMELS Simulations

Cosmology with Galaxy Photometry Alone

Pylians3: Libraries to analyze numerical simulations in Python 3

Francisco Villaescusa-Navarro Information

University

Position

___

Citations(all)

6893

Citations(since 2020)

5597

Cited By

3089

hIndex(all)

45

hIndex(since 2020)

41

i10Index(all)

97

i10Index(since 2020)

95

Email

University Profile Page

Google Scholar

Francisco Villaescusa-Navarro Skills & Research Interests

Astrophysics

cosmology

Machine Learning

Top articles of Francisco Villaescusa-Navarro

Atomic hydrogen shows its true colours: Correlations between HI and galaxy colour in simulations

arXiv preprint arXiv:2310.16884

2023/10/25

Benedikt Diemer
Benedikt Diemer

H-Index: 22

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Elena D'Onghia
Elena D'Onghia

H-Index: 22

Improving astrophysical scaling relations with machine learning

Bulletin of the American Physical Society

2024/4/3

Cosmological baryon spread and impact on matter clustering in CAMELS

Monthly Notices of the Royal Astronomical Society

2024/4

Debiasing with Diffusion: Probabilistic reconstruction of Dark Matter fields from galaxies with CAMELS

arXiv preprint arXiv:2403.10648

2024/3/15

Yueying Ni
Yueying Ni

H-Index: 7

Carolina Cuesta-Lazaro
Carolina Cuesta-Lazaro

H-Index: 3

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Zooming by in the CARPoolGP lane: new CAMELS-TNG simulations of zoomed-in massive halos

arXiv preprint arXiv:2403.10609

2024/3/15

Christopher Carr
Christopher Carr

H-Index: 17

Daisuke Nagai
Daisuke Nagai

H-Index: 39

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Probing the Circum-Galactic Medium with Fast Radio Bursts: Insights from the CAMELS Simulations

arXiv preprint arXiv:2403.02313

2024/3/4

Daisuke Nagai
Daisuke Nagai

H-Index: 39

Priyanka Singh
Priyanka Singh

H-Index: 3

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Cosmology with Galaxy Photometry Alone

arXiv preprint arXiv:2310.08634

2023/10/12

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Peter Melchior
Peter Melchior

H-Index: 57

Romain Teyssier
Romain Teyssier

H-Index: 58

Pylians3: Libraries to analyze numerical simulations in Python 3

Astrophysics Source Code Library

2024/3

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Quijote-PNG: Optimizing the summary statistics to measure Primordial non-Gaussianity

arXiv preprint arXiv:2403.00490

2024/3/1

Marco Baldi
Marco Baldi

H-Index: 19

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Taming assembly bias for primordial non-Gaussianity

Journal of Cosmology and Astroparticle Physics

2024/2/26

Licia Verde
Licia Verde

H-Index: 58

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Marco Baldi
Marco Baldi

H-Index: 19

Cosmological multifield emulator

arXiv preprint arXiv:2402.10997

2024/2/16

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

An observationally driven multifield approach for probing the circum-galactic medium with convolutional neural networks

Monthly Notices of the Royal Astronomical Society

2024/2

Daisuke Nagai
Daisuke Nagai

H-Index: 39

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Can we constrain warm dark matter masses with individual galaxies?

arXiv preprint arXiv:2401.17940

2024/1/31

A field-level emulator for modeling baryonic effects across hydrodynamic simulations

arXiv preprint arXiv:2401.15891

2024/1/29

Biwei Dai
Biwei Dai

H-Index: 3

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Uros Seljak
Uros Seljak

H-Index: 67

Signatures of a parity-violating universe

Physical Review D

2024/1/29

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Inferring warm dark matter masses with deep learning

Monthly Notices of the Royal Astronomical Society

2024/1

Paul Torrey
Paul Torrey

H-Index: 56

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Mark Vogelsberger
Mark Vogelsberger

H-Index: 67

Quijote-PNG: The Information Content of the Halo Mass Function

The Astrophysical Journal

2023/10/27

HaloGraphNet: Predict halo masses from simulations

Astrophysics Source Code Library

2023/3

Francisco Villaescusa-Navarro
Francisco Villaescusa-Navarro

H-Index: 30

Federico Marinacci
Federico Marinacci

H-Index: 50

Mark Vogelsberger
Mark Vogelsberger

H-Index: 67

Robust field-level likelihood-free inference with galaxies

The Astrophysical Journal

2023/7/18

The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites

The Astrophysical Journal

2023/12/14

See List of Professors in Francisco Villaescusa-Navarro University(Princeton University)