Carolina Cuesta-Lázaro

18 papers A 1Journal 14Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Augmenting representations with scientific papers.
CoRR
Nicolò Oreste Pinciroli Vago, Rocco Di Tella, Carolina Cuesta-Lázaro, Michael J. Smith, Cecilia Garraffo, Rafael Martínez-Galarza
2025 J jnl
CosmoFlow: Scale-Aware Representation Learning for Cosmology with Flow Matching.
CoRR
Sidharth Kannan, Tian Qiu, Carolina Cuesta-Lázaro, Haewon Jeong
2025 J jnl
Detecting Model Misspecification in Cosmology with Scale-Dependent Normalizing Flows.
CoRR
Aizhan Akhmetzhanova, Carolina Cuesta-Lázaro, Siddharth Mishra-Sharma
2025 J jnl
Detecting model misspecification in cosmology with scale-dependent normalizing flows.
Mach. Learn. Sci. Technol.
Aizhan Akhmetzhanova, Carolina Cuesta-Lázaro, Siddharth Mishra-Sharma
2024 J jnl
A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing.
CoRR
Julia Balla, Siddharth Mishra-Sharma, Carolina Cuesta-Lázaro, Tommi S. Jaakkola, Tess E. Smidt
2024 J jnl
Diffusion-HMC: Parameter Inference with Diffusion Model driven Hamiltonian Monte Carlo.
CoRR
Nayantara Mudur, Carolina Cuesta-Lázaro, Douglas P. Finkbeiner
2024 J jnl
How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds.
CoRR
Tri Nguyen, Francisco Villaescusa-Navarro, Siddharth Mishra-Sharma, Carolina Cuesta-Lázaro, Paul Torrey, Arya Farahi, Alex M. Garcia, Jonah C. Rose, Stephanie O'Neil, Mark Vogelsberger, Xuejian Shen, Cian Roche, Daniel Anglés-Alcázar, Nitya Kallivayalil, Julian B. Muñoz, Francis-Yan Cyr-Racine, Sandip Roy, Lina Necib, Kassidy E. Kollmann
2024 J jnl
LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology.
CoRR
Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier, Carolina Cuesta-Lázaro, Simon Ding, Axel Lapel, Pablo Lemos, Christopher C. Lovell, T. Lucas Makinen, Chirag Modi, Viraj Pandya, Shivam Pandey, Lucia A. Perez, Benjamin D. Wandelt, Greg L. Bryan
2023 J jnl
A point cloud approach to generative modeling for galaxy surveys at the field level.
CoRR
Carolina Cuesta-Lázaro, Siddharth Mishra-Sharma
2023 J jnl
Cosmological Field Emulation and Parameter Inference with Diffusion Models.
CoRR
Nayantara Mudur, Carolina Cuesta-Lázaro, Douglas P. Finkbeiner
2023 A conf
Don't Simulate Twice: One-Shot Sensitivity Analyses via Automatic Differentiation.
AAMAS
Arnau Quera-Bofarull, Ayush Chopra, Joseph Aylett-Bullock, Carolina Cuesta-Lázaro, Anisoara Calinescu, Ramesh Raskar, Michael J. Wooldridge
2023 J jnl
Probabilistic reconstruction of Dark Matter fields from biased tracers using diffusion models.
CoRR
Core Francisco Park, Victoria Ono, Nayantara Mudur, Yueying Ni, Carolina Cuesta-Lázaro
2023 — conf
Simulation-Based Inference for Exoplanet Atmospheric Retrieval: Insights from Winning the Ariel Data Challenge 2023 Using Normalizing Flows.
PKDD/ECML Workshops (5)
Mayeul Aubin, Carolina Cuesta-Lázaro, Ethan Tregidga, Javier Viaña, Cecilia Garraffo, Iouli E. Gordon, Mercedes López-Morales, Robert J. Hargreaves, Vladimir Yu. Makhnev, Jeremy J. Drake, Douglas P. Finkbeiner, Phillip Cargile
2023 J jnl
Simulation-based Inference for Exoplanet Atmospheric Retrieval: Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows.
CoRR
Mayeul Aubin, Carolina Cuesta-Lázaro, Ethan Tregidga, Javier Viaña, Cecilia Garraffo, Iouli E. Gordon, Mercedes López-Morales, Robert J. Hargreaves, Vladimir Yu. Makhnev, Jeremy J. Drake, Douglas P. Finkbeiner, Phillip Cargile
2022 — conf
What does the sea say to the shore? A BERT based DST style approach for speaker to dialogue attribution in novels.
ACL (1)
Carolina Cuesta-Lázaro, Animesh Prasad, Trevor Wood
2021 J jnl
Operational response simulation tool for epidemics within refugee and IDP settlements: A scenario-based case study of the Cox's Bazar settlement.
PLoS Comput. Biol.
Joseph Aylett-Bullock, Carolina Cuesta-Lázaro, Arnau Quera-Bofarull, Anjali Katta, Katherine Hoffmann Pham, Benjamin Hoover, Hendrik Strobelt, Rebeca Moreno Jimenez, Aidan Sedgewick, Egmond Samir Evers, David Kennedy, Sandra Harlass, Allen Gidraf Kahindo Maina, Ahmad Hussien, Miguel A. Luengo-Oroz
2019 — conf
XNet: a convolutional neural network (CNN) implementation for medical x-ray image segmentation suitable for small datasets.
Biomedical Applications in Molecular, Structural, and Functional Imaging
Joseph Bullock, Carolina Cuesta-Lázaro, Arnau Quera-Bofarull
2018 J jnl
XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets.
CoRR
Joseph Bullock, Carolina Cuesta-Lázaro, Arnau Quera-Bofarull