6 citations · 9 across the 17 of their papers we have counts for
6 papers · 1 filter
Internal Representations of Vision Models Through the Lens of Frames on Data Manifolds
Henry Kvinge, Grayson Jorgenson, Davis Brown +2
While the last five years have seen considerable progress in understanding the internal representations of deep learning models, many questions remain. This is especially true when…
Testing predictions of representation cost theory with CNNs
Charles Godfrey, Elise Bishoff, Myles Mckay +4
It is widely acknowledged that trained convolutional neural networks (CNNs) have different levels of sensitivity to signals of different frequency. In particular, a number of empir…
Pure subrings of Du Bois singularities are Du Bois singularities
Charles Godfrey, Takumi Murayama
Let be a cyclically pure map of Noetherian -algebras. In this paper, we show that if has Du Bois singularities, then has Du Bois singularities. Our re…
Higher direct images of snc ideal sheaves
Charles Godfrey
We prove invariance results for the cohomology groups of ideal sheaves of simple normal crossing divisors under (a restricted class of) birational morphisms of pairs in arbitrary c…
On the Symmetries of Deep Learning Models and their Internal Representations
Charles Godfrey, Davis Brown, Tegan Emerson +1
Symmetry is a fundamental tool in the exploration of a broad range of complex systems. In machine learning symmetry has been explored in both models and data. In this paper we seek…
Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps
Elizabeth Coda, Nico Courts, Colby Wight +6
While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as ma…