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Henry Kvinge
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Hypergraph models of biological networks to identify genes critical to pathogenic viral response
S Feng, E Heath, B Jefferson, C Joslyn, H Kvinge, HD Mitchell, ...
BMC Bioinformatics 22 (1), 1-21, 2021
1112021
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
382022
SCITUNE: Aligning Large Language Models with Scientific Multimodal Instructions
S Horawalavithana, S Munikoti, I Stewart, H Kvinge
arXiv preprint arXiv:2307.01139, 2023
242023
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?
H Kvinge, T Emerson, G Jorgenson, S Vasquez, T Doster, J Lew
Advances in Neural Information Processing Systems 35, 32816-32829, 2022
172022
Robustness of edited neural networks
D Brown, C Godfrey, C Nizinski, J Tu, H Kvinge
ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation …, 2023
162023
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
15*2023
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction
H Kvinge, E Farnell, M Kirby, C Peterson
2018 17th International Symposium on Parallel and Distributed Computing …, 2018
152018
Khovanov’s Heisenberg category, moments in free probability, and shifted symmetric functions
H Kvinge, AM Licata, S Mitchell
Algebraic Combinatorics 2 (1), 49-74, 2019
102019
Do neural networks trained with topological features learn different internal representations?
S McGuire, S Jackson, T Emerson, H Kvinge
NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 122-136, 2023
92023
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets
H Kvinge, E Farnell, M Kirby, C Peterson
2018 IEEE High Performance extreme Computing Conference (HPEC), 1-7, 2018
92018
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing
S Howland, L Kassab, K Kappagantula, H Kvinge, T Emerson
Integrating Materials and Manufacturing Innovation, 1-10, 2023
82023
Multi-dimensional scaling on groups
M Blumstein, H Kvinge
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
82021
A data-driven approach to sampling matrix selection for compressive sensing
E Farnell, H Kvinge, JP Dixon, JR Dupuis, M Kirby, C Peterson, ...
Computational Imaging V 11396, 1139603, 2020
82020
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
Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps
N Courts, H Kvinge
arXiv preprint arXiv:2110.06983, 2021
72021
Mathematical methods for visualization and anomaly detection in telemetry datasets
M Aminian, H Andrews-Polymenis, J Gupta, M Kirby, H Kvinge, X Ma, ...
Interface Focus 10 (1), 20190086, 2020
72020
ICML 2023 Topological Deep Learning Challenge: Design and Results
M Papillon, M Hajij, A Myers, F Frantzen, G Zamzmi, H Jenne, J Mathe, ...
Topological, Algebraic and Geometric Learning Workshops 2023, 3-8, 2023
62023
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
62023
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
62023
Sheaves as a Framework for Understanding and Interpreting Model Fit
H Kvinge, B Jefferson, C Joslyn, E Purvine
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
62021
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