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mit.edu
Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples | MIT Visualization Group
Embeddings mapping high-dimensional discrete input to lower-dimensional continuous vector spaces have been widely adopted in machine learning applications as a way to capture domain semantics. Interviewing 13 embedding users across disciplines, we find comparing embeddings is a key task for deployment or downstream analysis but unfolds in a ...
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