22 citations · 83 across the 12 of their papers we have counts for
8 papers · 1 filter
Wildfire risk forecast: An optimizable fire danger index
Eduardo Rodrigues, Bianca Zadrozny, Campbell Watson
Wildfire events have caused severe losses in many places around the world and are expected to increase with climate change. Throughout the years many technologies have been develop…
Addressing Deep Learning Model Uncertainty in Long-Range Climate Forecasting with Late Fusion
Ken C. L. Wong, Hongzhi Wang, Etienne E. Vos +3
Global warming leads to the increase in frequency and intensity of climate extremes that cause tremendous loss of lives and property. Accurate long-range climate prediction allows…
A comparative study of stochastic and deep generative models for multisite precipitation synthesis
Jorge Guevara, Dario Borges, Campbell Watson +1
Future climate change scenarios are usually hypothesized using simulations from weather generators. However, there only a few works comparing and evaluating promising deep learning…
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…
Decadal Forecasts with ResDMD: a Residual DMD Neural Network
Eduardo Rodrigues, Bianca Zadrozny, Campbell Watson +1
Operational forecasting centers are investing in decadal (1-10 year) forecast systems to support long-term decision making for a more climate-resilient society. One method that has…
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…
Bus Travel Time Predictions Using Additive Models
Matthias Kormaksson, Luciano Barbosa, Marcos R. Vieira +1
Many factors can affect the predictability of public bus services such as traffic, weather and local events. Other aspects, such as day of week or hour of day, may influence bus tr…
Predicting Conditional Quantiles via Reduction to Classification
John Langford, Roberto Oliveira, Bianca Zadrozny
We show how to reduce the process of predicting general order statistics (and the median in particular) to solving classification. The accompanying theoretical statement shows that…