David Lenz
Orcid: 0000-0002-2587-2783Affiliations:
- Argonne National Laboratory, Mathematics and Computer Science Division, Lemont, IL, USA
- University of California San Diego, CA, USA (PhD 2020)
According to our database1,
David Lenz
authored at least 17 papers
between 2020 and 2025.
Collaborative distances:
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Bibliography
2025
CoRR, July, 2025
F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding.
CoRR, July, 2025
Make the Fastest Faster: Importance Mask for Interactive Volume Visualization using Reconstruction Neural Networks.
CoRR, February, 2025
2024
Accelerating multivariate functional approximation computation with domain decomposition techniques.
J. Comput. Sci., 2024
Proceedings of the IEEE Topological Data Analysis and Visualization, 2024
Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024
Adaptive Multi-Resolution Encoding for Interactive Large-Scale Volume Visualization through Functional Approximation.
Proceedings of the 14th IEEE Symposium on Large Data Analysis and Visualization, 2024
2023
Math. Comput. Simul., November, 2023
J. Comput. Sci., 2023
Towards Adaptive Refinement for Multivariate Functional Approximation of Scientific Data.
Proceedings of the 13th IEEE Symposium on Large Data Analysis and Visualization, 2023
Scalable Volume Visualization for Big Scientific Data Modeled by Functional Approximation.
Proceedings of the IEEE International Conference on Big Data, 2023
2022
Parallel Domain Decomposition techniques applied to Multivariate Functional Approximation of discrete data.
CoRR, 2022
Proceedings of the Computational Science - ICCS 2022, 2022
2021
FTK: A Simplicial Spacetime Meshing Framework for Robust and Scalable Feature Tracking.
IEEE Trans. Vis. Comput. Graph., 2021
2020
FTK: A High-Dimensional Simplicial Meshing Framework for Robust and Scalable Feature Tracking.
CoRR, 2020