1.6k citations · 1.8k across the 4 of their papers we have counts for
4 papers
A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA
Benjamin Lucas, Behzad Vahedi, Morteza Karimzadeh
With COVID-19 affecting every country globally and changing everyday life, the ability to forecast the spread of the disease is more important than any previous epidemic. The conve…
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping
Benjamin Lucas, Charlotte Pelletier, Daniel Schmidt +2
Land cover maps are a vital input variable to many types of environmental research and management. While they can be produced automatically by machine learning techniques, these te…
InceptionTime: Finding AlexNet for Time Series Classification
Hassan Ismail Fawaz, Benjamin Lucas, Germain Forestier +7
This paper brings deep learning at the forefront of research into Time Series Classification (TSC). TSC is the area of machine learning tasked with the categorization (or labelling…
Proximity Forest: An effective and scalable distance-based classifier for time series
Benjamin Lucas, Ahmed Shifaz, Charlotte Pelletier +5
Research into the classification of time series has made enormous progress in the last decade. The UCR time series archive has played a significant role in challenging and guiding…