TorchSpatial: A Location Encoding Framework and Benchmark for Spatial
Representation Learning
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial
Representation Learning
Spatial representation learning (SRL) aims at learning general-purpose neural network representations from various types of spatial data (e.g., points, polylines, polygons, networks, images, etc.) in their native formats. Learning good spatial representations is a fundamental problem for various downstream applications such as species distribution modeling, weather forecasting, trajectory generation, geographic …