Optimal renormalization of multi-scale systems. - Jacob Price; Brek Meuris; Madelyn Shapiro; Panos Stinis (CoRR, 2021)

The SVD of Convolutional Weights: A CNN Interpretability Framework. - Brenda Praggastis; Davis Brown; Carlos Ortiz Marrero; Emilie Purvine; Madelyn Shapiro; Bei Wang 001 (CoRR, 2022)

Experimental Observations of the Topology of Convolutional Neural Network Activations. - Emilie Purvine; Davis Brown; Brett A. Jefferson; Cliff A. Joslyn; Brenda Praggastis; Archit Rathore; Madelyn Shapiro; Bei Wang 001; Youjia Zhou (AAAI, 2023)

Topological Analysis of Temporal Hypergraphs. - Audun Myers; Cliff A. Joslyn; Bill Kay; Emilie Purvine; Gregory Roek; Madelyn Shapiro (WAW, 2023)

Attributing Learned Concepts in Neural Networks to Training Data. - Nicholas Konz; Charles Godfrey; Madelyn Shapiro; Jonathan H. Tu; Henry Kvinge; Davis Brown (CoRR, 2023)

Neural Differential Algebraic Equations. - James Koch; Madelyn Shapiro; Himanshu Sharma; Draguna L. Vrabie; Ján Drgona (CoRR, 2024)

Model editing for distribution shifts in uranium oxide morphological analysis. - Davis Brown; Cody Nizinski; Madelyn Shapiro; Corey Fallon; Tianzhixi Yin; Henry Kvinge; Jonathan H. Tu (CoRR, 2024)

HyperNetX: A Python package for modeling complex network data as hypergraphs. - Brenda Praggastis; Sinan Aksoy; Dustin Arendt; Mark Bonicillo; Cliff A. Joslyn; Emilie Purvine; Madelyn Shapiro; Ji Young Yun (J. Open Source Softw., 2024)