AI RESEARCH
Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves
arXiv CS.LG
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ArXi:2605.06395v1 Announce Type: new Modern deep learning architectures increasingly contend with sophisticated signals that are natively infinite-dimensional, such as time series, probability distributions, or operators, and are defined over irregular domains. Yet, a unified learning theory for these settings has been lacking. To start addressing this gap, we