Efficient Classification of Seismic Textures. - Daniel Salles Chevitarese; Daniela Szwarcman; Emilio Vital Brazil; Bianca Zadrozny (IJCNN, 2018)

Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency. - Daniela Szwarcman; Daniel Civitarese; Marley M. B. R. Vellasco (BRACIS, 2019)

Quantum-Inspired Neural Architecture Search. - Daniela Szwarcman; Daniel Civitarese; Marley M. B. R. Vellasco (IJCNN, 2019)

Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation. - Laís Baroni; Reinaldo Mozart Da Gama e Silva; Rodrigo S. Ferreira; Daniel Civitarese; Daniela Szwarcman; Emilio Vital Brazil (CoRR, 2019)

Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation. - Reinaldo Mozart Da Gama e Silva; Laís Baroni; Rodrigo S. Ferreira; Daniel Civitarese; Daniela Szwarcman; Emilio Vital Brazil (CoRR, 2019)

Semantic Segmentation of Seismic Images. - Daniel Civitarese; Daniela Szwarcman; Emilio Vital Brazil; Bianca Zadrozny (CoRR, 2019)

A modular framework for extreme weather generation. - Bianca Zadrozny; Campbell D. Watson; Daniela Szwarcman; Daniel Civitarese; Dário A. B. Oliveira; Eduardo Rodrigues; Jorge Guevara Diaz (CoRR, 2021)

Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network. - Daniel Salles Civitarese; Daniela Szwarcman; Bianca Zadrozny; Campbell D. Watson (CoRR, 2021)

Enabling Robust Horizon Picking From Small Training Sets. - Andréa Britto Mattos; Daniel Civitarese; Daniela Szwarcman; Matheus Oliveira; Semen Zaytsev; Daniil Semin; Dário A. B. Oliveira (IEEE Trans. Geosci. Remote. Sens., 2021)

Quantum-inspired evolutionary algorithm applied to neural architecture search. - Daniela Szwarcman; Daniel Civitarese; Marley M. B. R. Vellasco (Appl. Soft Comput., 2022)

Generating physically-consistent high-resolution climate data with hard-constrained neural networks. - Paula Harder; Qidong Yang; Venkatesh Ramesh; Prasanna Sattigeri; Alex Hernández-García; Campbell D. Watson; Daniela Szwarcman; David S. Rolnick (CoRR, 2022)

Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling. - Qidong Yang; Alex Hernández-García; Paula Harder; Venkatesh Ramesh; Prasanna Sattigeri; Daniela Szwarcman; Campbell D. Watson; David Rolnick (CoRR, 2023)

Foundation Models for Generalist Geospatial Artificial Intelligence. - 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; et al. (CoRR, 2023)

A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network. - Takuya Kurihana; Kyongmin Yeo; Daniela Szwarcman; Bruce Elmegreen; S. Karthik Mukkavilli; Johannes Schmude; Levente J. Klein (CoRR, 2023)

Hard-Constrained Deep Learning for Climate Downscaling. - Paula Harder; Alex Hernández-García; Venkatesh Ramesh; Qidong Yang; Prasanna Sattegeri; Daniela Szwarcman; Campbell D. Watson; David Rolnick (J. Mach. Learn. Res., 2023)

Fine-tuning of Geospatial Foundation Models for Aboveground Biomass Estimation. - 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; et al. (CoRR, 2024)

Evaluating the transferability potential of deep learning models for climate downscaling. - Ayush Prasad; Paula Harder; Qidong Yang; Prasanna Sattegeri; Daniela Szwarcman; Campbell D. Watson; David Rolnick (CoRR, 2024)

Prithvi WxC: Foundation Model for Weather and Climate. - 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; et al. (CoRR, 2024)

Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications. - 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; et al. (CoRR, 2024)

TerraTorch: The Geospatial Foundation Models Toolkit. - 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 (CoRR, 2025)