SMU Reading GroupTopics in Applied Math and Data Science |
Version | v0.1.0 | |
|---|---|---|---|
| Updated | 2025-01-23 | ||
| Author | Mason A. McCallum, Marc de Vernon | License | MIT |
Welcome to the Applied Math Journal Club! The club is open to anyone interested in learning modern topics of applied math. Selected topics for the upcoming semester will include uncertainty quantification, inverse problems, generative modeling in scientific computing, numerics for high-dimensional PDE, and data-driven equation discovery. If you have any questions about the club, please contact us..
| Topic | Discussion Leader | Date | Supplementary Materials |
|---|---|---|---|
| Algorithmic Differentiation | Mason McCallum | Feb 3rd, 2025 | TBA |
| TBA | TBA | Feb 10th, 2025 | N/A |
| TBA | Austin Marstaller | Feb 24th, 2025 | N/A |
| TBA | John Levis | Mar 24th, 2025 | N/A |
| Differentiable Programming | Mason McCallum | Mar 31st, 2025 | N/A |
| TBA | Daniel Margolis | April 7th, 2025 | N/A |
| TBA | TBA | April 7th, 2025 | N/A |
| TBA | TBA | Feb 21st, 2025 | N/A |
| TBA | TBA | Feb 28th, 2025 | N/A |
| Topic | Discussion Leader | Date | Supplementary Materials |
|---|---|---|---|
| Random NLA | Jimmie Adriazola | Nov 19th, 2024 | N/A |
| Neural ODEs | Andrew Ho | Nov 12th, 2024 | N/A |
| POD | Marc DeVernon | Oct. 22nd, 2024 | N/A |
| RSVD | Mason McCallum | Oct. 15th, 2024 | N/A |
| KAM Networks | Mason McCallum | Oct. 1st, 2024 | notes |
| SympNets | Andrew Ho | Sep. 24th, 2024 | N/A |
| Math Bio | Md Abu Talha | Sep. 10th, 2024 | N/A |
| Welcome Meeting | Jimmie Adriazola | Sep. 3rd, 2024 | N/A |
| Optimal Transport and Applications (Research Talk) | Axel Turnquist (UT Austin) | April 16, 2024 | |
| Flow-based generative models for Markov chain Monte Carlo in lattice field theory | Jimmie Adriazola | April 9, 2024 | Notes, Code |
| Solving high-dimensional partial differential equations using deep learning | Daniel Margolis | March 26, 2024 | Notes, Slides |
| Predicting nonlinear dynamics of optical solitons in optical fiber via the SCPINN | Sabrina Hetzel | March 19, 2024 | Code |
| A Mean-Field Games Laboratory for Generative Modeling | Jimmie Adriazola | March 5, 2024 | Notes |
| A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems | Jimmie Adriazola | February 27, 2024 | Notes |
| Discovering governing equations from partial measurements with deep delay autoencoders | Mason McCallum | February 13, 2024 | Notes/Code |
| Discovering governing equations from partial measurements with deep delay autoencoders | Mason McCallum | February 6, 2024 | - |
| Denoising Diffusion Probabilistic Models | Jimmie Adriazola | January 23, 2024 | Notes |
| The Bayesian Approach To Inverse Problems | Austin Marstaller | January 16, 2024 | Slides |
| The Modern Mathematics of Deep Learning, Berner, et al. | Jimmie Adriazola | December 4, 2023 | Notes |
| The Modern Mathematics of Deep Learning, Berner, et al. | Jimmie Adriazola | November 20, 2023 | Notes |
| Organizational Meeting | N/A | October 23, 2023 | N/A |
What Kinds of Functions Do Deep Neural Networks Learn? Insights from Variational Spline Theory
Solving high-dimensional partial differential equations using deep learning
Score-Based Generative Modeling through Stochastic Differential Equations
In-context operator learning with data prompts for differential equation problems
Approximation rates for neural networks with general activation functions
I would like to acknowledge Jimmie Adriazola for mentoring and guiding the formation of this reading group. Marc Devernon for managing the webpage. This webpage is a fork of: https://github.com/owickstrom/the-monospace-web.git So much thanks to Oskar Wickstrom for the nice work