We study ways to recognize when data recorded in different ways represents the same information. Why? Because better comparisons allow for smaller data sets, improving search times and decreasing storage needs. But also we enjoy the challenge of working on a century old question, tested on the first commercial computers, and a vexing puzzle to modern researchers. This is equal parts math, computer science, and computation.
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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