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Davis Brown
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2020 – today
- 2024
- [i15]Davis Brown, Cody Nizinski, Madelyn Shapiro, Corey Fallon, Tianzhixi Yin, Henry Kvinge, Jonathan H. Tu:
Model editing for distribution shifts in uranium oxide morphological analysis. CoRR abs/2407.15756 (2024) - 2023
- [c5]Emilie Purvine, Davis Brown, Brett A. Jefferson, Cliff A. Joslyn, Brenda Praggastis, Archit Rathore, Madelyn Shapiro
, Bei Wang, Youjia Zhou:
Experimental Observations of the Topology of Convolutional Neural Network Activations. AAAI 2023: 9470-9479 - [c4]Davis Brown, Henry Kvinge:
Making Corgis Important for Honeycomb Classification: Adversarial Attacks on Concept-based Explainability Tools. CVPR Workshops 2023: 620-627 - [c3]Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler:
How many dimensions are required to find an adversarial example? CVPR Workshops 2023: 2353-2360 - [c2]Davis Brown, Charles Godfrey, Nicholas Konz, Jonathan H. Tu, Henry Kvinge:
Understanding the Inner-workings of Language Models Through Representation Dissimilarity. EMNLP 2023: 6543-6558 - [i14]Henry Kvinge, Davis Brown, Charles Godfrey:
Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension. CoRR abs/2302.09301 (2023) - [i13]Davis Brown, Charles Godfrey, Cody Nizinski, Jonathan H. Tu, Henry Kvinge:
Robustness of edited neural networks. CoRR abs/2303.00046 (2023) - [i12]Charles Godfrey, Michael G. Rawson, Davis Brown, Henry Kvinge:
Fast computation of permutation equivariant layers with the partition algebra. CoRR abs/2303.06208 (2023) - [i11]Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler
How many dimensions are required to find an adversarial example? CoRR abs/2303.14173 (2023) - [i10]Davis Brown, Nikhil Vyas, Yamini Bansal:
On Privileged and Convergent Bases in Neural Network Representations. CoRR abs/2307.12941 (2023) - [i9]Nicholas Konz
Attributing Learned Concepts in Neural Networks to Training Data. CoRR abs/2310.03149 (2023) - [i8]Davis Brown, Charles Godfrey, Nicholas Konz, Jonathan H. Tu, Henry Kvinge:
Understanding the Inner Workings of Language Models Through Representation Dissimilarity. CoRR abs/2310.14993 (2023) - [i7]Cody Tipton, Elizabeth Coda, Davis Brown, Alyson Bittner, Jung H. Lee, Grayson Jorgenson, Tegan Emerson
Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus. CoRR abs/2312.04600 (2023) - 2022
- [c1]Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge:
On the Symmetries of Deep Learning Models and their Internal Representations. NeurIPS 2022 - [i6]Charles Godfrey
On the Symmetries of Deep Learning Models and their Internal Representations. CoRR abs/2205.14258 (2022) - [i5]Brenda Praggastis, Davis Brown, Carlos Ortiz Marrero, Emilie Purvine, Madelyn Shapiro, Bei Wang:
The SVD of Convolutional Weights: A CNN Interpretability Framework. CoRR abs/2208.06894 (2022) - [i4]Charles Godfrey
Convolutional networks inherit frequency sensitivity from image statistics. CoRR abs/2210.01257 (2022) - [i3]Henry Kvinge, Grayson Jorgenson, Davis Brown, Charles Godfrey
Neural frames: A Tool for Studying the Tangent Bundles Underlying Image Datasets and How Deep Learning Models Process Them. CoRR abs/2211.10558 (2022) - [i2]Emilie Purvine, Davis Brown, Brett A. Jefferson
Experimental Observations of the Topology of Convolutional Neural Network Activations. CoRR abs/2212.00222 (2022) - 2021
- [i1]Davis Brown, Henry Kvinge
Brittle interpretations: The Vulnerability of TCAV and Other Concept-based Explainability Tools to Adversarial Attack. CoRR abs/2110.07120 (2021)
Coauthor Index
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