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Journal Articles
- 2023
[j3]Paula Harder, Alex Hernández-García, Venkatesh Ramesh, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick:
Hard-Constrained Deep Learning for Climate Downscaling. J. Mach. Learn. Res. 24: 365:1-365:40 (2023)- 2022
- [j2]Daniela Szwarcman
, Daniel Civitarese, Marley M. B. R. Vellasco:
Quantum-inspired evolutionary algorithm applied to neural architecture search. Appl. Soft Comput. 120: 108674 (2022) - 2021
- [j1]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): 5317-5324 (2021)
Conference and Workshop Papers
- 2019
- [c3]Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco:
Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency. BRACIS 2019: 509-514 - [c2]Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco:
Quantum-Inspired Neural Architecture Search. IJCNN 2019: 1-8 - 2018
- [c1]Daniel Salles Chevitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny:
Efficient Classification of Seismic Textures. IJCNN 2018: 1-8
Informal and Other Publications
- 2024
- [i12]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:
Fine-tuning of Geospatial Foundation Models for Aboveground Biomass Estimation. CoRR abs/2406.19888 (2024) - [i11]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 abs/2407.12517 (2024) - [i10]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:
Prithvi WxC: Foundation Model for Weather and Climate. CoRR abs/2409.13598 (2024) - 2023
- [i9]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 abs/2305.14452 (2023) - [i8]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 abs/2310.18660 (2023) - [i7]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 abs/2312.13212 (2023) - 2022
- [i6]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 abs/2208.05424 (2022) - 2021
- [i5]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 abs/2102.04534 (2021) - [i4]Daniel Salles Civitarese, Daniela Szwarcman, Bianca Zadrozny, Campbell D. Watson:
Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network. CoRR abs/2107.06846 (2021) - 2019
- [i3]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 abs/1903.12060 (2019) - [i2]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 abs/1904.00770 (2019) - [i1]Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny:
Semantic Segmentation of Seismic Images. CoRR abs/1905.04307 (2019)
Coauthor Index
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