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cs.LG2024
Model editing for distribution shifts in uranium oxide morphological analysis
Davis Brown, Cody Nizinski, Madelyn Shapiro +4
Deep learning still struggles with certain kinds of scientific data. Notably, pretraining data may not provide coverage of relevant distribution shifts (e.g., shifts induced via th…
cs.LG2023
Attributing Learned Concepts in Neural Networks to Training Data
Nicholas Konz, Charles Godfrey, Madelyn Shapiro +3
By now there is substantial evidence that deep learning models learn certain human-interpretable features as part of their internal representations of data. As having the right (or…
cs.LG2022
Experimental Observations of the Topology of Convolutional Neural Network Activations
Emilie Purvine, Davis Brown, Brett Jefferson +6
Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of compl…