4 papers
Construction and Evaluation of Machine Learning Models for Near-Real-Time Fire Detection from MTG FCI Imagery
Asaf Vanunu, Boaz Nadler, Arnon Karnieli
Geostationary satellite observations are important for wildfire detection and monitoring. The current study evaluates machine learning models for MTG FCI near-real-time fire detect…
Comparing a gradient boosting algorithm to the GOES FDC for wildfire detection
Asaf Vanunu, Boaz Nadler, Arnon Karnieli
Wildfires pose severe risks to human life, ecosystems, and property. This study presents a machine learning approach for wildfire detection from GOES ABI imagery. A CatBoost model…
SDSR: A Spectral Divide-and-Conquer Approach for Species Tree Reconstruction
Ortal Reshef, Ofer Glassman, Or Zuk +3
Recovering a tree that represents the evolutionary history of a group of species is a key task in phylogenetics. Performing this task using sequence data from multiple genetic mark…
Robustness of OLS to sample removals: Theoretical analysis and implications
Eyar Azar, Michael J. Feldman, Boaz Nadler
For learned models to be trustworthy, it is essential to verify their robustness to perturbations in the training data. Classical approaches involve uncertainty quantification via…