% 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}, }