Cecilia Garraffo

According to our database, Cecilia Garraffo authored at least 9 papers between 2023 and 2026.

Collaborative distances:

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

2026

Plume Segmentation from MethaneSAT with Cross-Sensor Transfer Learning and Physics-Informed Postprocessing.

Manuel Perez-Carrasco, Maya Nasr, Zhan Zhang, Apisada Chulakadabba, Javier Roger, Raia Ottenheimer, Sebastien Roche, Maryann Sargent, Chris Chan Miller, Daniel Varon, Jack Warren, Luis Guanter, Kang Sun, Jonathan Franklin, Jia Chen, Cecilia Garraffo, Xiong Liu, Ritesh Gautam, Steven Wofsy

CoRR, May, 2026

Augmenting representations with scientific papers.

Nicolò Oreste Pinciroli Vago, Rocco Di Tella, Carolina Cuesta-Lázaro, Michael J. Smith, Cecilia Garraffo, Rafael Martínez-Galarza

CoRR, March, 2026

Variational Autoencoder with Normalizing flow for X-ray spectral fitting.

Fiona Redmen, Ethan Tregidga, James F. Steiner, Cecilia Garraffo

CoRR, January, 2026

Denoising Hamiltonian Network for Physical Reasoning.

Congyue Deng, Brandon Y. Feng, Cecilia Garraffo, Alan Garbarz, Robin Walters, William T. Freeman, Leonidas J. Guibas, Kaiming He

Trans. Mach. Learn. Res., 2026

2025

Hyperspectral Variational Autoencoders for Joint Data Compression and Component Extraction.

Core Francisco Park, Manuel Perez-Carrasco, Caroline Nowlan, Cecilia Garraffo

CoRR, November, 2025

Deep Learning for Clouds and Cloud Shadow Segmentation in Methane Satellite and Airborne Imaging Spectroscopy.

Manuel Perez-Carrasco, Maya Nasr, Sebastien Roche, Chris Chan Miller, Zhan Zhang, Core Francisco Park, Eleanor Walker, Cecilia Garraffo, Douglas P. Finkbeiner, Ritesh Gautam, Steven Wofsy

CoRR, September, 2025

The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS).

Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella S. R. Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang

CoRR, September, 2025

2023

Generating Images of the M87* Black Hole Using GANs.

Arya Mohan, Pavlos Protopapas, Keerthi Kunnumkai, Cecilia Garraffo, Lindy Blackburn, Koushik Chatterjee, Sheperd S. Doeleman, Razieh Emami, Christian M. Fromm, Yosuke Mizuno, Angelo Ricarte

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