Daniela Szwarcman

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 16

Top Topics

Neural Architecture

Machine Learning

Top Venues

IEEE Trans. Geosci. Remote. Sens.

Publications

Ayush Prasad, Paula Harder, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
Evaluating the transferability potential of deep learning models for climate downscaling. CoRR (2024)
Michal Muszynski, Levente 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
Fine-tuning of Geospatial Foundation Models for Aboveground Biomass Estimation. CoRR (2024)
Takuya Kurihana, Kyongmin Yeo, Daniela Szwarcman, Bruce Elmegreen, S. Karthik Mukkavilli, Johannes Schmude, Levente J. Klein
A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network. CoRR (2023)
Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling. CoRR (2023)
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
Foundation Models for Generalist Geospatial Artificial Intelligence. CoRR (2023)
Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri, Alex Hernández-García, Campbell D. Watson, Daniela Szwarcman, David S. Rolnick
Generating physically-consistent high-resolution climate data with hard-constrained neural networks. CoRR (2022)
Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco
Quantum-inspired evolutionary algorithm applied to neural architecture search. Appl. Soft Comput. 120 (2022)
Bianca Zadrozny, Campbell D. Watson, Daniela Szwarcman, Daniel Civitarese, Dário A. B. Oliveira, Eduardo Rodrigues, Jorge Guevara Diaz
A modular framework for extreme weather generation. CoRR (2021)
Daniel Salles Civitarese, Daniela Szwarcman, Bianca Zadrozny, Campbell D. Watson
Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network. CoRR (2021)
Andréa Britto Mattos, Daniel Civitarese, Daniela Szwarcman, Matheus Oliveira, Semen Zaytsev, Daniil Semin, Dário A. B. Oliveira
Enabling Robust Horizon Picking From Small Training Sets. IEEE Trans. Geosci. Remote. Sens. 59 (6) (2021)
Lais Baroni, Reinaldo Mozart Da Gama e Silva, Rodrigo S. Ferreira, Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil
Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation. CoRR (2019)
Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny
Semantic Segmentation of Seismic Images. CoRR (2019)
Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco
Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency. BRACIS (2019)
Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco
Quantum-Inspired Neural Architecture Search. IJCNN (2019)
Reinaldo Mozart Da Gama e Silva, Lais Baroni, Rodrigo S. Ferreira, Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil
Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation. CoRR (2019)
Daniel Salles Chevitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny
Efficient Classification of Seismic Textures. IJCNN (2018)