Math and ML Reading Group - Spring Semester 2024
Welcome to our series of talks regarding mathematical foundation of neural networks and machine learning. Below is the schedule for the upcoming semester.
Location: Evans 762 from 2 pm to 3 pm on Fridays (Zoom upon request). To access Zoom sessions, please email me.
Organizers: Franny Dean, Lewis Pan, and Maksym Zubkov.
Goals: These reading group aim to delve deep into the latest advancements in mathematical foundation of machine learning and neural networks.
Below are the possible articles we're considering:
| # | Date | Topic | Speaker | Links |
|---|---|---|---|---|
| 1 | February 9 | Organizational meeting | ||
| 2 | February 16 | Geometry of Deep Polynomial Neural Networks | Maksym Zubkov | slides, recording, code |
| 3 | February 23 |
Deep Learning Essentials: From Universal Approximation to Backpropagation and Beyond |
Joshua Benjamin | slides, recording, code |
| 4 | March 1 | AI for Health Inspired by Physics Informed Neural Networks | Franny Dean | slides |
| 5 | March 8 | Practical Introduction to Classification | Lewis Pan | |
| 6 | March 15 | How Might a Computer Learn a Physical Law | Daniel Chupin | |
| 7 | March 22 | Transformers: More Than Meets AI | Brian Cruz | slides |
| 8 | March 29 | Spring Break | ||
| 9 | April 5 | Natural vs. Artificial Intelligence | Vladimir Baranovsky | recording |
| 10 | April 12 | Using NNs to Solve Macroeconomic Models | Anna Vakarova | |
| 11 | April 19 | How to Fake Just About Anything: Variational Autoencoders | Daniel Chupin | notes |
| 12 | April 26 | Safety & LLM | Adam Dhillon |
