Jeff Calder
Associate Professor of Mathematics538 Vincent Hall
School of Mathematics
University of Minnesota
Phone: 612-626-1324
Email: jcalder at umn dot edu
Recent Talks
Below is a list of recent talks that I have given, along with the slides and links to videos of the talks, when available. My recent IMA Data Science seminar talk, available here, describes a lot of my research on graph learning over the past few years. For a full list please refer to my CV.- 1. Boundary estimation and Hamilton-Jacobi equations on point clouds [Slides]
- Mathematical Data Science Seminar, Purdue University, April 2022.
- Mathematics Colloquium, University of Utah, April 2022.
- Minisymposium on the geometry of PDEs on graphs: analysis and applications, SIAM Conference on Analysis of PDEs, March 2022.
- Hamilton-Jacobi PDEs Reunion Conference I, Institute for Pure and Applied Mathematics, January 2022.
- 2. Uniform convergence rates for Lipschitz learning down to graph connectivity
- Workshop on Dynamics and Discretization: PDEs, Sampling, and Optimization, Simons Institute for the Theory of Computing, October 2021. [Video]
- 3. Random walks and PDEs in graph-based learning [Slides]
- Applied Mathematics Seminar, University of Texas at San Antonio, November 2021.
- Seminar on the Mathematics of Deep Learning, FAU Erlangen-Nürnberg, May 2021.
- Applied Mathematics Seminar, Courant Institute, New York University, April 2021
- The Mathematics of Machine Learning, One World Seminar Series, March 2021 [Video]
- Computational and Applied Mathematics Seminar, Tufts University, March 2021.
- Applied Mathematics Colloquium, New Jersey Institute of Technology, January 2021.
- Mathematics Colloquium, University of Toronto, January 2021.
- CSE/DTC Machine Learning Seminar, University of Minnesota, Sept 2020 [Video]
- School of Mathematics Colloquium, University of Minnesota, Sept 2020.
- Mathematics in Imaging, Data and Optimization Seminar, Rensselaer Polytechnic Institute (RPI), Sept 2020.
- Workshop on PDE and Inverse Problem Methods in Machine Learning, Institute for Pure and Applied Mathematics, April 2020.
- Center for Nonlinear Analysis Seminar, Carnegie Mellon University, February 2020.
- 4. Poisson Learning: A framework for graph-based semi-supervised learning at very low label rates [Slides]
- Minisymposium on Theory and applications of graph-based learning, SIAM Conference on Computational Science and Engineering, March 2021.
- International Conference on Machine Learning (ICML), July 2020
- 5. PDE continuum limits for prediction with expert advice [Slides]
- ICMS Workshop on Analytic and Geometric Approaches to Machine Learning, University of Bath, July 2021.
- Nonlinear Analysis Seminar, Rutgers University, April 2021.
- Stochastics and PDEs Seminar, University of Jyväskylä, March 2021.
- Applied and Computational Analysis Seminar, University of Cambridge, June 2019.
- Workshop on Inverse Problems and Machine Learning, Center de reserches mathematiques, Montreal, May 2019.
- 6. Discrete regularity for graph Laplacians [Slides]
- Workshop on Stochastic Analysis Related to Hamilton-Jacobi PDEs, Institute for Pure and Applied Mathematics, May 2020. [Video]
- 7. Computation of integral invariants for geometry processing with applications to analysis of broken bone fragments [Slides]
- Symposium on Computational Modeling and Image Processing of Biomedical Problems, Michigan Technological University, June 2019.
- 8. Nonlinear PDE continuum limits in data science and machine learning [Slides]
- PDE & Geometric Analysis Seminar, University of Wisconsin Madison, April 2018.
- 9. Introduction to Concentration of Measure with applications to graph-based learning.
- Long program on High Dimensional Hamilton-Jacobi Equations, Institute for Pure and Applied Mathematics (IPAM). Video: [Part 1][Part 2]