Learning sparse codes from compressed representations with biologically plausible local wiring constraints

1 code implementation • NeurIPS 2020 • Kion Fallah, Adam Willats, Ninghao Liu, Christopher Rozell

Unfortunately, current proposals for sparse coding in the compressed space require a centralized compression process (i. e., dense random matrix) that is biologically unrealistic due to local wiring constraints observed in neural circuits.

Dimensionality Reduction