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Davis Brown
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Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning
V Sagan, M Maimaitijiang, S Bhadra, M Maimaitiyiming, DR Brown, ...
ISPRS journal of photogrammetry and remote sensing 174, 265-281, 2021
1272021
On the symmetries of deep learning models and their internal representations
C Godfrey, D Brown, T Emerson, H Kvinge
Advances in Neural Information Processing Systems 35, 11893-11905, 2022
332022
Edit at your own risk: evaluating the robustness of edited models to distribution shifts
D Brown, C Godfrey, C Nizinski, J Tu, H Kvinge
arXiv preprint arXiv:2303.00046, 2023
13*2023
Making corgis important for honeycomb classification: adversarial attacks on concept-based explainability tools
D Brown, H Kvinge
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
12*2023
The SVD of convolutional weights: a CNN interpretability framework
B Praggastis, D Brown, CO Marrero, E Purvine, M Shapiro, B Wang
arXiv preprint arXiv:2208.06894, 2022
122022
Experimental observations of the topology of convolutional neural network activations
E Purvine, D Brown, B Jefferson, C Joslyn, B Praggastis, A Rathore, ...
Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9470-9479, 2023
112023
Understanding the inner workings of language models through representation dissimilarity
D Brown, C Godfrey, N Konz, J Tu, H Kvinge
arXiv preprint arXiv:2310.14993, 2023
72023
On privileged and convergent bases in neural network representations
D Brown, N Vyas, Y Bansal
arXiv preprint arXiv:2307.12941, 2023
52023
Fast computation of permutation equivariant layers with the partition algebra
C Godfrey, MG Rawson, D Brown, H Kvinge
arXiv preprint arXiv:2303.06208, 2023
42023
Exploring the representation manifolds of stable diffusion through the lens of intrinsic dimension
H Kvinge, D Brown, C Godfrey
arXiv preprint arXiv:2302.09301, 2023
42023
How many dimensions are required to find an adversarial example?
C Godfrey, H Kvinge, E Bishoff, M Mckay, D Brown, T Doster, E Byler
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
32023
Comparing Mapper Graphs of Artificial Neuron Activations
Y Zhou, H Jenne, D Brown, M Shapiro, B Jefferson, C Joslyn, ...
2023 Topological Data Analysis and Visualization (TopoInVis), 41-50, 2023
22023
Internal representations of vision models through the lens of frames on data manifolds
H Kvinge, G Jorgenson, D Brown, C Godfrey, T Emerson
NeurIPS 2023 Workshop on Symmetry and Geometry in Neural Representations, 2023
1*2023
Wild Comparisons: A Study of how Representation Similarity Changes when Input Data is Drawn from a Shifted Distribution
D Brown, MR Shapiro, A Bittner, J Warley, H Kvinge
ICLR 2024 Workshop on Representational Alignment, 2024
2024
Model editing for distribution shifts in uranium oxide morphological analysis
D Brown, C Nizinski, M Shapiro, C Fallon, T Yin, H Kvinge, JH Tu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
2024
Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus
C Tipton, E Coda, D Brown, A Bittner, J Lee, G Jorgenson, T Emerson, ...
arXiv preprint arXiv:2312.04600, 2023
2023
DeepDataProfiler: A Platform and Methodology for the Analysis and Interpretation of Neural Networks
BL Praggastis, DR Brown, EAH Purvine, MR Shapiro, B Wang
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States), 2023
2023
Attributing Learned Concepts in Neural Networks to Training Data
N Konz, C Godfrey, M Shapiro, J Tu, H Kvinge, D Brown
arXiv preprint arXiv:2310.03149, 2023
2023
pnnl/frequency_sensitivity
C Godfrey, E Bishoff, M McKay, D Brown, G Jorgenson, H Kvinge, N Byler
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States), 2023
2023
pnnl/modelsym
C Godfrey, D Brown, T Emerson, H Kvinge
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States), 2022
2022
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