Henry Kvinge
Orcid: 0000-0003-4108-1364Affiliations:
- Pacific Northwest National Laboratory, Richland, WA, USA
- University of Washington, Department of Mathematics, Seattle, WA, USA
- Colorado State University, Fort Collins, CO, USA
- University of California Davis, CA, USA (PhD)
According to our database1,
Henry Kvinge
authored at least 52 papers
between 2018 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
CoRR, 2024
CoRR, 2024
2023
Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus.
CoRR, 2023
CoRR, 2023
ColMix - A Simple Data Augmentation Framework to Improve Object Detector Performance and Robustness in Aerial Images.
CoRR, 2023
CoRR, 2023
Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension.
CoRR, 2023
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing.
CoRR, 2023
Proceedings of the Topological, 2023
Understanding the Inner-workings of Language Models Through Representation Dissimilarity.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
TopFusion: Using Topological Feature Space for Fusion and Imputation in Multi-Modal Data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Making Corgis Important for Honeycomb Classification: Adversarial Attacks on Concept-based Explainability Tools.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Neural frames: A Tool for Studying the Tangent Bundles Underlying Image Datasets and How Deep Learning Models Process Them.
CoRR, 2022
CoRR, 2022
Proceedings of the Topological, 2022
Random Filters for Enriching the Discriminatory power of Topological Representations.
Proceedings of the Topological, 2022
Proceedings of the Topological, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Do neural networks trained with topological features learn different internal representations?
Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022
Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps.
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing.
CoRR, 2021
Brittle interpretations: The Vulnerability of TCAV and Other Concept-based Explainability Tools to Adversarial Attack.
CoRR, 2021
CoRR, 2021
Rotating spiders and reflecting dogs: a class conditional approach to learning data augmentation distributions.
CoRR, 2021
One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations.
CoRR, 2021
CoRR, 2021
Hypergraph models of biological networks to identify genes critical to pathogenic viral response.
BMC Bioinform., 2021
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning.
Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021
2020
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
2019
More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing.
CoRR, 2019
CoRR, 2019
CoRR, 2019
A Walk Through Spectral Bands: Using Virtual Reality to Better Visualize Hyperspectral Data.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019
2018
Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets.
CoRR, 2018
Proceedings of the 17th International Symposium on Parallel and Distributed Computing, 2018
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets.
Proceedings of the 2018 IEEE High Performance Extreme Computing Conference, 2018
Proceedings of the 2018 IEEE Data Science Workshop, 2018
Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large datasets.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018