Publications (6)
TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting
Natalia Ponomareva, Soroush Radpour, Gilbert Hendry +4
TF Boosted Trees (TFBT) is a new open-sourced frame-work for the distributed training of gradient boosted trees. It is based on TensorFlow, and its distinguishing features include…
Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning
Aaron Bell, Amit Aides, Amr Helmy +57
Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales, and spars…
Fast Approximate Determinants Using Rational Functions
Thomas Colthurst, Srinivas Vasudevan, James Lottes +1
We show how rational function approximations to the logarithm, such as , can be turned into fast algorithms for approximating the determina…
A Gray path on binary partitions
Thomas Colthurst, Michael Kleber
A binary partition of a positive integer is a partition of in which each part has size a power of two. In this note we first construct a Gray sequence on the set of binary…
Compact Multi-Class Boosted Trees
Natalia Ponomareva, Thomas Colthurst, Gilbert Hendry +2
Gradient boosted decision trees are a popular machine learning technique, in part because of their ability to give good accuracy with small models. We describe two extensions to th…
Estimating Residential Solar Potential Using Aerial Data
Ross Goroshin, Alex Wilson, Andrew Lamb +9
Project Sunroof estimates the solar potential of residential buildings using high quality aerial data. That is, it estimates the potential solar energy (and associated financial sa…