39 citations · 113 across the 8 of their papers we have counts for
8 papers
Foundation Models for Generalist Geospatial Artificial Intelligence
Johannes Jakubik, Sujit Roy, C. E. Phillips +30
Significant progress in the development of highly adaptable and reusable Artificial Intelligence (AI) models is expected to have a significant impact on Earth science and remote se…
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling
Qidong Yang, Alex Hernandez-Garcia, Paula Harder +5
Climate simulations are essential in guiding our understanding of climate change and responding to its effects. However, it is computationally expensive to resolve complex climate…
Hard-Constrained Deep Learning for Climate Downscaling
Paula Harder, Alex Hernandez-Garcia, Venkatesh Ramesh +5
The availability of reliable, high-resolution climate and weather data is important to inform long-term decisions on climate adaptation and mitigation and to guide rapid responses…
Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network
Daniel Salles Civitarese, Daniela Szwarcman, Bianca Zadrozny +1
An impact of climate change is the increase in frequency and intensity of extreme precipitation events. However, confidently predicting the likelihood of extreme precipitation at s…
A modular framework for extreme weather generation
Bianca Zadrozny, Campbell D. Watson, Daniela Szwarcman +4
Extreme weather events have an enormous impact on society and are expected to become more frequent and severe with climate change. In this context, resilience planning becomes cruc…
Semantic Segmentation of Seismic Images
Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil +1
Almost all work to understand Earth's subsurface on a large scale relies on the interpretation of seismic surveys by experts who segment the survey (usually a cube) into layers; a…
Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation
Reinaldo Mozart Silva, Lais Baroni, Rodrigo S. Ferreira +3
Machine learning and, more specifically, deep learning algorithms have seen remarkable growth in their popularity and usefulness in the last years. This is arguably due to three ma…
Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation
Lais Baroni, Reinaldo Mozart Silva, Rodrigo S. Ferreira +3
We have seen in the past years the flourishing of machine and deep learning algorithms in several applications such as image classification and segmentation, object detection and r…