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stat.ML2026
Persistent Convolution: A Topological Framework for AI Alignment Testing and Semantic Space Characterization
Tyler Ashoff, Jordan Rodu
Modern opaque AI models prize performance over interpretability, which makes testing difficult. However, formal statistical tests conducted on a model's embedding space can provide…
stat.ML2023
Change Point Detection with Conceptors
Noah D. Gade, Jordan Rodu
Offline change point detection retrospectively locates change points in a time series. Many nonparametric methods that target i.i.d. mean and variance changes fail in the presence…