Daniela Szwarcman

21 papers B 2Journal 18Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
TerraTorch: The Geospatial Foundation Models Toolkit.
CoRR
Carlos Gomes, Benedikt Blumenstiel, João Lucas de Sousa Almeida, Pedro Henrique de Oliveira, Paolo Fraccaro, Francesc Marti Escofet, Daniela Szwarcman, Naomi Simumba, Romeo Kienzler, Bianca Zadrozny
2024 J jnl
Evaluating the transferability potential of deep learning models for climate downscaling.
CoRR
Ayush Prasad, Paula Harder, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2024 J jnl
Fine-tuning of Geospatial Foundation Models for Aboveground Biomass Estimation.
CoRR
Michal Muszynski, Levente J. Klein, Ademir Ferreira da Silva, Anjani Prasad Atluri, Carlos Gomes, Daniela Szwarcman, Gurkanwar Singh, Kewen Gu, Maciel Zortea, Naomi Simumba, Paolo Fraccaro, Shraddha Singh, Steve Meliksetian, Campbell D. Watson, Daiki Kimura, Harini Srinivasan
2024 J jnl
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling.
J. Mach. Learn. Res.
Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2024 J jnl
Prithvi WxC: Foundation Model for Weather and Climate.
CoRR
Johannes Schmude, Sujit Roy, Will Trojak, Johannes Jakubik, Daniel Salles Civitarese, Shraddha Singh, Julian Kuehnert, Kumar Ankur, Aman Gupta, Christopher Phillips, Romeo Kienzler, Daniela Szwarcman, Vishal Gaur, Rajat Shinde, Rohit Lal, Arlindo Da Silva, Jorge Luis Guevara Diaz, Anne Jones, Simon Pfreundschuh, Amy Lin, Aditi Sheshadri, Udaysankar Nair, Valentine Anantharaj, Hendrik F. Hamann, Campbell D. Watson, Manil Maskey, Tsengdar J. Lee, Juan Bernabé-Moreno, Rahul Ramachandran
2024 J jnl
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications.
CoRR
Daniela Szwarcman, Sujit Roy, Paolo Fraccaro, Þorsteinn Elí Gíslason, Benedikt Blumenstiel, Rinki Ghosal, Pedro Henrique de Oliveira, João Lucas de Sousa Almeida, Rocco Sedona, Yanghui Kang, Srija Chakraborty, Sizhe Wang, Ankur Kumar, Myscon Truong, Denys Godwin, Hyunho Lee, Chia-Yu Hsu, Ata Akbari Asanjan, Besart Mujeci, Trevor Keenan, Paulo Arévalo, Wenwen Li, Hamed Alemohammad, Pontus Olofsson, Christopher Hain, Robert Kennedy, Bianca Zadrozny, Gabriele Cavallaro, Campbell D. Watson, Manil Maskey, Rahul Ramachandran, Juan Bernabé-Moreno
2023 J jnl
A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network.
CoRR
Takuya Kurihana, Kyongmin Yeo, Daniela Szwarcman, Bruce Elmegreen, S. Karthik Mukkavilli, Johannes Schmude, Levente J. Klein
2023 J jnl
Foundation Models for Generalist Geospatial Artificial Intelligence.
CoRR
Johannes Jakubik, Sujit Roy, C. E. Phillips, Paolo Fraccaro, Denys Godwin, Bianca Zadrozny, Daniela Szwarcman, Carlos Gomes, Gabby Nyirjesy, Blair Edwards, Daiki Kimura, Naomi Simumba, Linsong Chu, S. Karthik Mukkavilli, Devyani Lambhate, Kamal Das, Ranjini Bangalore, Dário A. B. Oliveira, Michal Muszynski, Kumar Ankur, Muthukumaran Ramasubramanian, Iksha Gurung, Sam Khallaghi, Hanxi Li, Michael Cecil, Maryam Ahmadi, Fatemeh Kordi, Hamed Alemohammad, Manil Maskey, Raghu K. Ganti, Kommy Weldemariam, Rahul Ramachandran
2023 J jnl
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling.
CoRR
Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2023 J jnl
Hard-Constrained Deep Learning for Climate Downscaling.
J. Mach. Learn. Res.
Paula Harder, Alex Hernández-García, Venkatesh Ramesh, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2022 J jnl
Generating physically-consistent high-resolution climate data with hard-constrained neural networks.
CoRR
Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri, Alex Hernández-García, Campbell D. Watson, Daniela Szwarcman, David S. Rolnick
2022 J jnl
Quantum-inspired evolutionary algorithm applied to neural architecture search.
Appl. Soft Comput.
Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco
2021 J jnl
A modular framework for extreme weather generation.
CoRR
Bianca Zadrozny, Campbell D. Watson, Daniela Szwarcman, Daniel Civitarese, Dário A. B. Oliveira, Eduardo Rodrigues, Jorge Guevara Diaz
2021 J jnl
Enabling Robust Horizon Picking From Small Training Sets.
IEEE Trans. Geosci. Remote. Sens.
Andréa Britto Mattos, Daniel Civitarese, Daniela Szwarcman, Matheus Oliveira, Semen Zaytsev, Daniil Semin, Dário A. B. Oliveira
2021 J jnl
Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network.
CoRR
Daniel Salles Civitarese, Daniela Szwarcman, Bianca Zadrozny, Campbell D. Watson
2019 J jnl
Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation.
CoRR
Reinaldo Mozart Da Gama e Silva, Laís Baroni, Rodrigo S. Ferreira, Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil
2019 J jnl
Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation.
CoRR
Laís Baroni, Reinaldo Mozart Da Gama e Silva, Rodrigo S. Ferreira, Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil
2019 — conf
Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency.
BRACIS
Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco
2019 B conf
Quantum-Inspired Neural Architecture Search.
IJCNN
Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco
2019 J jnl
Semantic Segmentation of Seismic Images.
CoRR
Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny
2018 B conf
Efficient Classification of Seismic Textures.
IJCNN
Daniel Salles Chevitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny