Jeffrey W Calder

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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.

Fingerprint The Fingerprint is created by mining the titles and abstracts of the person's research outputs and projects/funding awards to create an index of weighted terms from discipline-specific thesauri.

Continuum Limit Mathematics
Semi-supervised Learning Mathematics
Supervised learning Engineering & Materials Science
Numerical Scheme Mathematics
Sorting Engineering & Materials Science
Partial differential equation Mathematics
Graph Laplacian Mathematics
Streaming Data Mathematics

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Projects 2016 2021

Monotone Scheme
Semi-supervised Learning
Scaling Limit
Nonlinear Partial Differential Equations
Numerical Scheme

Calder: Corning

Calder, J. W.



Project: Research project

Continuum Limit
Nonlinear Partial Differential Equations

Research Output 2009 2019

1 Citation (Scopus)

Accelerated Variational PDEs for Efficient Solution of Regularized Inversion Problems

Benyamin, M., Calder, J., Sundaramoorthi, G. & Yezzi, A., Jan 1 2019, (Accepted/In press) In : Journal of Mathematical Imaging and Vision.

Research output: Contribution to journalArticle

pulse detonation engines
Efficient Solution
Wave equations

PDE acceleration: a convergence rate analysis and applications to obstacle problems

Calder, J. & Yezzi, A., Dec 1 2019, In : Research in Mathematical Sciences. 6, 4, 35.

Research output: Contribution to journalArticle

Obstacle Problem
Convergence Rate
Complexity Analysis
Wave equations
Equations of motion

Properly-Weighted Graph Laplacian for Semi-supervised Learning

Calder, J. & Slepčev, D., Jan 1 2019, (Accepted/In press) In : Applied Mathematics and Optimization.

Research output: Contribution to journalArticle

Graph Laplacian
Semi-supervised Learning
Supervised learning
Weighted Graph
Learning algorithms
2 Citations (Scopus)

The game theoretic p-Laplacian and semi-supervised learning with few labels

Calder, J., Jan 2019, In : Nonlinearity. 32, 1, p. 301-330 30 p.

Research output: Contribution to journalArticle

Semi-supervised Learning
Laplace equation
Supervised learning
2 Citations (Scopus)

Anomaly detection and classification for streaming data using pdes*

Abbasi, B., Calder, J. & Oberman, A. M., Jan 1 2018, In : SIAM Journal on Applied Mathematics. 78, 2, p. 921-941 21 p.

Research output: Contribution to journalArticle

Streaming Data
Anomaly Detection
Partial differential equations
Partial differential equation