2026
A Network of Biologically Inspired Rectified Spectral Units (ReSUs) Learns Hierarchical Features Without Error Backpropagation
Shanshan Qin, Joshua L. Pughe-Sanford, Alexander Genkin, Pembe Gizem Ozdil, Philip Greengard, Anirvan M. Sengupta +1
AAAI 2026technical
We introduce a biologically inspired, multilayer neural architecture composed of Rectified Spectral Units (ReSUs). Each ReSU projects a recent window of its input history onto a canonical direction obtained via canonical correlation analysis (CCA) of previously observed past–future input pairs, and