Francisco Villaescusa-Navarro

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 25

Top Topics

Adaptive Kalman Filter

Symbolic Regression

Top Venues

Astron. Comput.

Publications

Natalí S. M. de Santi, Francisco Villaescusa-Navarro, L. Raul Abramo, Helen Shao, Lucia A. Perez, Tiago Castro, Yueying Ni, Christopher C. Lovell, Elena Hernandez-Martinez, Federico Marinacci, David N. Spergel, Klaus Dolag, Lars Hernquist, Mark Vogelsberger
Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects. CoRR (2023)
Natalí S. M. de Santi, Helen Shao, Francisco Villaescusa-Navarro, L. Raul Abramo, Romain Teyssier, Pablo Villanueva-Domingo, Yueying Ni, Daniel Anglés-Alcázar, Shy Genel, Elena Hernandez-Martinez, Ulrich P. Steinwandel, Christopher C. Lovell, Klaus Dolag, Tiago Castro, Mark Vogelsberger
Robust field-level likelihood-free inference with galaxies. CoRR (2023)
Yueying Ni, Shy Genel, Daniel Anglés-Alcázar, Francisco Villaescusa-Navarro, Yongseok Jo, Simeon Bird, Tiziana di Matteo, Rupert A. C. Croft, Nianyi Chen, Natalí S. M. de Santi, Matthew Gebhardt, Helen Shao, Shivam Pandey, Lars Hernquist, Romeel Dave
The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites. CoRR (2023)
Andrea Roncoli, Aleksandra Ciprijanovic, Maggie Voetberg, Francisco Villaescusa-Navarro, Brian Nord
Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets. CoRR (2023)
Drew Jamieson, Yin Li, Siyu He, Francisco Villaescusa-Navarro, Shirley Ho, Renan Alves de Oliveira, David N. Spergel
Simple lessons from complex learning: what a neural network model learns about cosmic structure formation. CoRR (2022)
Pablo Villanueva-Domingo, Francisco Villaescusa-Navarro
Learning cosmology and clustering with cosmic graphs. CoRR (2022)
Digvijay Wadekar, Leander Thiele, Francisco Villaescusa-Navarro, J. Colin Hill, David N. Spergel, Miles D. Cranmer, Nicholas Battaglia, Daniel Anglés-Alcázar, Lars Hernquist, Shirley Ho
Augmenting astrophysical scaling relations with machine learning : application to reducing the SZ flux-mass scatter. CoRR (2022)
Drew Jamieson, Yin Li, Renan Alves de Oliveira, Francisco Villaescusa-Navarro, Shirley Ho, David N. Spergel
Field Level Neural Network Emulator for Cosmological N-body Simulations. CoRR (2022)
Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lucia A. Perez, Pablo Villanueva-Domingo, Digvijay Wadekar, Helen Shao, Faizan G. Mohammad, Sultan Hassan, Emily Moser, Erwin T. Lau, Luis Fernando Machado Poletti Valle, Andrina Nicola, Leander Thiele, Yongseok Jo, Oliver H. E. Philcox, Benjamin D. Oppenheimer, Megan Tillman, ChangHoon Hahn, Neerav Kaushal, Alice Pisani, Matthew Gebhardt, Ana Maria Delgado, Joyce Caliendo, Christina Kreisch, Kaze W. K. Wong, William R. Coulton, Michael Eickenberg, Gabriele Parimbelli, Yueying Ni, Ulrich P. Steinwandel, Valentina La Torre, Romeel Dave, Nicholas Battaglia, Daisuke Nagai, David N. Spergel, Lars Hernquist, Blakesley Burkhart, Desika Narayanan, Benjamin D. Wandelt, Rachel S. Somerville, Greg L. Bryan, Matteo Viel, Yin Li, Vid Irsic, Katarina Kraljic, Mark Vogelsberger
The CAMELS project: public data release. CoRR (2022)
Cora Dvorkin, Siddharth Mishra-Sharma, Brian Nord, V. Ashley Villar, Camille Avestruz, Keith Bechtol, Aleksandra Ciprijanovic, Andrew J. Connolly, Lehman H. Garrison, Gautham Narayan, Francisco Villaescusa-Navarro
Machine Learning and Cosmology. CoRR (2022)
Digvijay Wadekar, Leander Thiele, J. Colin Hill, Shivam Pandey, Francisco Villaescusa-Navarro, David N. Spergel, Miles D. Cranmer, Daisuke Nagai, Daniel Anglés-Alcázar, Shirley Ho, Lars Hernquist
The SZ flux-mass (Y-M) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback. CoRR (2022)
Davide Piras, Benjamin Joachimi, Francisco Villaescusa-Navarro
Fast and realistic large-scale structure from machine-learning-augmented random field simulations. CoRR (2022)
Helen Shao, Francisco Villaescusa-Navarro, Pablo Villanueva-Domingo, Romain Teyssier, Lehman H. Garrison, Marco Gatti, Derek Inman, Yueying Ni, Ulrich P. Steinwandel, Mihir Kulkarni, Eli Visbal, Greg L. Bryan, Daniel Angles-Alcazar, Tiago Castro, Elena Hernandez-Martinez, Klaus Dolag
Robust field-level inference with dark matter halos. CoRR (2022)
Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, David N. Spergel, Yin Li, Benjamin D. Wandelt, Andrina Nicola, Leander Thiele, Sultan Hassan, José Manuel Zorrilla Matilla, Desika Narayanan, Romeel Dave, Mark Vogelsberger
Multifield Cosmology with Artificial Intelligence. CoRR (2021)
Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar, David N. Spergel, Yin Li, Benjamin D. Wandelt, Leander Thiele, Andrina Nicola, José Manuel Zorrilla Matilla, Helen Shao, Sultan Hassan, Desika Narayanan, Romeel Dave, Mark Vogelsberger
Robust marginalization of baryonic effects for cosmological inference at the field level. CoRR (2021)
Pablo Villanueva-Domingo, Francisco Villaescusa-Navarro, Daniel Anglés-Alcázar, Shy Genel, Federico Marinacci, David N. Spergel, Lars Hernquist, Mark Vogelsberger, Romeel Dave, Desika Narayanan
Inferring halo masses with Graph Neural Networks. CoRR (2021)
Francisco Villaescusa-Navarro, Shy Genel, Daniel Angles-Alcazar, Leander Thiele, Romeel Dave, Desika Narayanan, Andrina Nicola, Yin Li, Pablo Villanueva-Domingo, Benjamin D. Wandelt, David N. Spergel, Rachel S. Somerville, José Manuel Zorrilla Matilla, Faizan G. Mohammad, Sultan Hassan, Helen Shao, Digvijay Wadekar, Michael Eickenberg, Kaze W. K. Wong, Gabriella Contardo, Yongseok Jo, Emily Moser, Erwin T. Lau, Luis Fernando Machado Poletti Valle, Lucia A. Perez, Daisuke Nagai, Nicholas Battaglia, Mark Vogelsberger
The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence. CoRR (2021)
Pablo Villanueva-Domingo, Francisco Villaescusa-Navarro, Shy Genel, Daniel Anglés-Alcázar, Lars Hernquist, Federico Marinacci, David N. Spergel, Mark Vogelsberger, Desika Narayanan
Weighing the Milky Way and Andromeda with Artificial Intelligence. CoRR (2021)
Chang Chen, Yin Li, Francisco Villaescusa-Navarro, Shirley Ho, Anthony Pullen
Learning the Evolution of the Universe in N-body Simulations. CoRR (2020)
T. Lucas Makinen, Lachlan Lancaster, Francisco Villaescusa-Navarro, Peter Melchior, Shirley Ho, Laurence Perreault Levasseur, David N. Spergel
deep21: a Deep Learning Method for 21cm Foreground Removal. CoRR (2020)
Renan Alves de Oliveira, Yin Li, Francisco Villaescusa-Navarro, Shirley Ho, David N. Spergel
Fast and Accurate Non-Linear Predictions of Universes with Deep Learning. CoRR (2020)
Xinyue Zhang, Yanfang Wang, Wei Zhang, Yueqiu Sun, Siyu He, Gabriella Contardo, Francisco Villaescusa-Navarro, Shirley Ho
From Dark Matter to Galaxies with Convolutional Networks. CoRR (2019)
Jacky H. T. Yip, Xinyue Zhang, Yanfang Wang, Wei Zhang, Yueqiu Sun, Gabriella Contardo, Francisco Villaescusa-Navarro, Siyu He, Shy Genel, Shirley Ho
From Dark Matter to Galaxies with Convolutional Neural Networks. CoRR (2019)
Elena Giusarma, Mauricio Reyes Hurtado, Francisco Villaescusa-Navarro, Siyu He, Shirley Ho, ChangHoon Hahn
Learning neutrino effects in Cosmology with Convolutional Neural Networks. CoRR (2019)
Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro, Seda Bilaloglu, Asena Derin Cengiz, Siyu He, Laurence Perreault Levasseur, Shirley Ho
HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks. CoRR (2019)
Paul M. Sutter, Guilhem Lavaux, Nico Hamaus, Alice Pisani, Benjamin D. Wandelt, Michael S. Warren, Francisco Villaescusa-Navarro, Paul Zivick, Qingqing Mao, Benjamin B. Thompson
VIDE: The Void IDentification and Examination toolkit. Astron. Comput. 9 (2015)