How can we recognize that data recorded in different ways represents the same information? Better comparisons allow for smaller data sets, improve search times and decreasing storage needs.
This is the question of isomorphism and it has been a hard problem for more than century. We are focussed on cases where the data is parameterized by vector spaces and the differences are changes of bases. That is, we study any data with an obvious or hidden distributive law.
This is a place for our tools, results, tutorials, and workshop videos, and a list of activities to come. Tucked inside are many interesting by-products (decompositions, tensor space compression, search algorithms, random models, and exotic constructions). Feel free to share these, give us feedback, and to get involved in improvements.
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