151 citations · 191 across the 5 of their papers we have counts for
5 papers
Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior
John Burge, Matthew R. Bonanni, R. Lily Hu +1
The increasing incidence and severity of wildfires underscores the necessity of accurately predicting their behavior. While high-fidelity models derived from first principles offer…
Accelerating Physics Simulations with TPUs: An Inundation Modeling Example
Damien Pierce, R. Lily Hu, Yusef Shafi +4
Recent advancements in hardware accelerators such as Tensor Processing Units (TPUs) speed up computation time relative to Central Processing Units (CPUs) not only for machine learn…
Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data
Fantine Huot, R. Lily Hu, Nita Goyal +3
Predicting wildfire spread is critical for land management and disaster preparedness. To this end, we present `Next Day Wildfire Spread,' a curated, large-scale, multivariate data…
Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data
Fantine Huot, R. Lily Hu, Matthias Ihme +6
Identifying regions that have high likelihood for wildfires is a key component of land and forestry management and disaster preparedness. We create a data set by aggregating nearly…
Image Segmentation to Distinguish Between Overlapping Human Chromosomes
R. Lily Hu, Jeremy Karnowski, Ross Fadely +1
In medicine, visualizing chromosomes is important for medical diagnostics, drug development, and biomedical research. Unfortunately, chromosomes often overlap and it is necessary t…