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Davis Brown
Davis Brown
在 pnnl.gov 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
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
1152021
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
262022
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
11*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
112022
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
10*2023
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
82023
On privileged and convergent bases in neural network representations
D Brown, N Vyas, Y Bansal
arXiv preprint arXiv:2307.12941, 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
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
32023
Fast computation of permutation equivariant layers with the partition algebra
C Godfrey, MG Rawson, D Brown, H Kvinge
arXiv preprint arXiv:2303.06208, 2023
32023
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
22023
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
12023
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, 2022
1*2022
Model editing for distribution shifts in uranium oxide morphological analysis
D Brown, C Nizinski, M Shapiro, C Fallon, T Yin, H Kvinge, JH Tu
arXiv preprint arXiv:2407.15756, 2024
2024
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
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
Testing predictions of representation cost theory with CNNs
C Godfrey, E Bishoff, M Mckay, D Brown, G Jorgenson, H Kvinge, E Byler
arXiv preprint arXiv:2210.01257, 2022
2022
Convolutional networks inherit frequency sensitivity from image statistics.
C Godfrey, E Bishoff, M Mckay, D Brown, G Jorgenson, H Kvinge, E Byler
CoRR, 2022
2022
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