SOURCE-LINKED INTELLIGENCE
Chronosphere: Space-Time Tessellation of Local Climate Experts
We introduce Chronosphere, a spatio-temporal neural field that learns representations of climate. A central challenge in geographic representation learning is modeling environmental processes whose spatial and temporal complexity varies widely. Yet existing location encoders typically fix a single level of detail everywhere. Global bases such as spherical harmonics spread capacity uniformly across space and time. Localized bases resolve only predefined regions. Learned tessellations adapt, but are inefficient at representing higher frequencies. Chronosphere unifies these approaches, pairing an
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T15:00:08.000Z
First collected: 2026-09-23T13:51:27.104Z. This is not the publication date.