Projects per year
Personal profile
Research interests
My research involves interactions between partial differential equations (PDE), numerical schemes, applied probability, and computer science. I am interested in both the rigorous analysis of PDE, and the development and implementation of algorithms. It is exciting when mathematical analysis and insights can lead to more efficient algorithms. A continuing theme in my current research is finding continuum limits for discrete combinatorial problems. I am particularly interested when these continuum limits involve solving nonlinear PDEs, and have applications in science and engineering.
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Collaborations and top research areas from the last five years
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MoDL: Analytical Foundations for Deep Learning and Inference over Graphs
THE NATIONAL SCIENCE FOUNDATION
7/1/22 → 6/30/25
Project: Research project
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CAREER: Harnessing the continuum for big data: Partial differential equations, calculus of variations and machine learning
THE NATIONAL SCIENCE FOUNDATION
7/1/20 → 6/30/25
Project: Research project
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Geometric Analysis for Classification and Reassembly of Broken Bones
Olver, P. J. & Calder, J.
THE NATIONAL SCIENCE FOUNDATION
9/1/18 → 8/31/21
Project: Research project
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Deep Semi-supervised Label Propagation for SAR Image Classification
Enwright, J., Hardiman-Mostow, H., Calder, J. & Bertozzi, A., 2023, Algorithms for Synthetic Aperture Radar Imagery XXX. Zelnio, E. & Garber, F. D. (eds.). SPIE, 125200G. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 12520).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Novel Batch Active Learning Approach and Its Application to Synthetic Aperture Radar Datasets
Chapman, J., Chen, B., Tan, Z., Calder, J., Miller, K. & Bertozzi, A. L., 2023, Algorithms for Synthetic Aperture Radar Imagery XXX. Zelnio, E. & Garber, F. D. (eds.). SPIE, 125200B. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 12520).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
2 Scopus citations -
Online Prediction with History-Dependent Experts: The General Case
Drenska, N. & Calder, J., Sep 2023, In: Communications on Pure and Applied Mathematics. 76, 9, p. 1678-1727 50 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Scopus citations -
Rates of convergence for Laplacian semi-supervised learning with low labeling rates
Calder, J., Slepčev, D. & Thorpe, M., Mar 2023, In: Research in Mathematical Sciences. 10, 1, 10.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Uniform convergence rates for Lipschitz learning on graphs
Bungert, L., Calder, J. & Roith, T., Jul 1 2023, In: IMA Journal of Numerical Analysis. 43, 4, p. 2445-2495 51 p.Research output: Contribution to journal › Article › peer-review
Datasets
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GraphLearning Python Package
Calder, J., ZENODO, 2022
DOI: 10.5281/zenodo.5850940, https://zenodo.org/record/5850940
Dataset