Applied Mathematics/Data Science Journal Club
Welcome to the Applied Math/Data Science Journal Club! The club is open to anyone interested in learning what applied math has to say about data science or recent machine learning methods that have already made a great impact on scientific computing. Selected topics so far include applied analysis of neural networks, data-driven equation discovery, generative modeling, and numerics for high-dimensional PDE. If you have any questions about the club, please contact us.
Spring semester meetings will take place on Tuesdays at 3:00 P.M. in Moody Hall Room 241Club Schedule: Fall 2023
| Topic/Article | Discussion Leader | Date | Supplementary Materials |
|---|---|---|---|
| Organizational Meeting | N/A | October 23, 2023 | N/A |
| The Modern Mathematics of Deep Learning, Berner, et al. | Jimmie Adriazola | November 20, 2023 | Notes |
| The Modern Mathematics of Deep Learning, Berner, et al. | Jimmie Adriazola | December 4, 2023 | Notes |
Club Schedule: Spring 2024
Suggested Future Readings:
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