% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@INPROCEEDINGS{Renner:1024857,
author = {Renner, Alpha and Supic, Lazar and Danielescu, Andreea and
Indiveri, Giacomo and Olshausen, Bruno A. and Sandamirskaya,
Yulia and Sommer, Friedrich T. and Paxon Frady, E.},
title = {{N}euromorphic {H}yperdimensional {V}isual {S}cene
{F}actorization},
reportid = {FZJ-2024-02523},
year = {2023},
abstract = {In this talk at NNPC 2023, I will present a modular
neuromorphic algorithm leveraging recent advancements in
hyperdimensional computing/ Vector Symbolic Architectures
(VSAs).VSAs have been proposed as a framework for symbolic
reasoning, spatial, and graph operations on neuromorphic
hardware. They make use of a small set of computational
primitives that are robust, efficient, and compatible with
diverse hardware. Our algorithm approaches scene
understanding as a factorization problem and employs the
resonator network to extract object identities and
transformations. This is achieved by reflecting the
algebraic structure of 2d rigid transforms (translations and
rotation) in the neural VSA representation. Finally, we use
a spike-timing-based implementation of phasor neurons to
show an efficient proof of concept implementation on
neuromorphic hardware and employ the model in a robotics
task for visual odometry (visual SLAM).},
month = {Oct},
date = {2023-10-25},
organization = {International conference on
neuromorphic, natural and physical
computing, Hannover (Germany), 25 Oct
2023 - 27 Oct 2023},
subtyp = {After Call},
cin = {PGI-15},
cid = {I:(DE-Juel1)PGI-15-20210701},
pnm = {5234 - Emerging NC Architectures (POF4-523)},
pid = {G:(DE-HGF)POF4-5234},
typ = {PUB:(DE-HGF)6},
doi = {10.34734/FZJ-2024-02523},
url = {https://juser.fz-juelich.de/record/1024857},
}