Carolina Cuesta-Lázaro

According to our database, Carolina Cuesta-Lázaro authored at least 12 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing.

Julia Balla, Siddharth Mishra-Sharma, Carolina Cuesta-Lázaro, Tommi S. Jaakkola, Tess E. Smidt

CoRR, 2024

How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds.

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

CoRR, 2024

Diffusion-HMC: Parameter Inference with Diffusion Model driven Hamiltonian Monte Carlo.

Nayantara Mudur, Carolina Cuesta-Lázaro, Douglas P. Finkbeiner

CoRR, 2024

LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology.

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

CoRR, 2024

2023

Cosmological Field Emulation and Parameter Inference with Diffusion Models.

Nayantara Mudur, Carolina Cuesta-Lázaro, Douglas P. Finkbeiner

CoRR, 2023

A point cloud approach to generative modeling for galaxy surveys at the field level.

Carolina Cuesta-Lázaro, Siddharth Mishra-Sharma

CoRR, 2023

Probabilistic reconstruction of Dark Matter fields from biased tracers using diffusion models.

Core Francisco Park, Victoria Ono, Nayantara Mudur, Yueying Ni, Carolina Cuesta-Lázaro

CoRR, 2023

Simulation-Based Inference for Exoplanet Atmospheric Retrieval: Insights from Winning the Ariel Data Challenge 2023 Using Normalizing Flows.

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

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023

Don't Simulate Twice: One-Shot Sensitivity Analyses via Automatic Differentiation.

Arnau Quera-Bofarull, Ayush Chopra, Joseph Aylett-Bullock, Carolina Cuesta-Lázaro, Anisoara Calinescu, Ramesh Raskar, Michael J. Wooldridge

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022

What does the sea say to the shore? A BERT based DST style approach for speaker to dialogue attribution in novels.

Carolina Cuesta-Lázaro, Animesh Prasad, Trevor Wood

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Operational response simulation tool for epidemics within refugee and IDP settlements: A scenario-based case study of the Cox's Bazar settlement.

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

PLoS Comput. Biol., 2021

2019

XNet: a convolutional neural network (CNN) implementation for medical x-ray image segmentation suitable for small datasets.

Joseph Bullock, Carolina Cuesta-Lázaro, Arnau Quera-Bofarull

Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019