Tile2Vec: Unsupervised representation learning for spatially distributed data

8 May 2018Neal JeanSherrie WangAnshul SamarGeorge AzzariDavid LobellStefano Ermon

Geospatial analysis lacks methods like the word vector representations and pre-trained networks that significantly boost performance across a wide range of natural language and computer vision tasks. To fill this gap, we introduce Tile2Vec, an unsupervised representation learning algorithm that extends the distributional hypothesis from natural language -- words appearing in similar contexts tend to have similar meanings -- to spatially distributed data... (read more)

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