Sheaves are the canonical datastructure for sensor integration · HackerPapers discussions

Sheaves are the canonical datastructure for sensor integration — mentioned by zmgsabst

Sun, 25 Dec 2022 13:04:41 GMT

Michael Robinson is the person I know working on this topic — and who I borrowed the phrasing from. https://www.drmichaelrobinson.net/sheaftutorial/ https://arxiv.org/abs/1603.01446

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Sheaves are the canonical datastructure for sensor integration — mentioned by pizza

Tue, 07 Mar 2017 18:08:43 GMT

Thanks for posting the sheaf talks a while back, been getting into em. Also found this he made https://arxiv.org/abs/1603.01446

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Sheaves are the canonical datastructure for sensor integration — mentioned by espeed

Sun, 19 Feb 2017 00:57:03 GMT

A sheaf is a combinatorial, high-dimensional data structure on a topological space. You can use it to stitch together images, spatio-temporal target tracking, inference, data fusion, IoT time-series, continuous functions -- all kinds of things. Crazy cool stuff! Applied sheaf theory is pretty new, and not yet widely known. This DARPA sheaf tutorial is a full two-day video series by Prof Michael Robinson (great teacher), and it's about the equivalent of a semester CS course compressed into two days. If you want to see an intro/big-picture overview video on what the sheaf data structure is, and…

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Sheaves are the canonical datastructure for sensor integration — HN submission

Sat, 18 Feb 2017 21:12:05 GMT

Sheaves are the canonical data structure for sensor integration

2 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.