Black Box Lectures
In the summer, interns, students, and faculty gather for Black Box Lectures. Each lecture covers an area of interest in machine learning, statistics, computer science, and artificial intelligence. The idea is to look under the hood of "black box" models and methods.
Each lecture will be a chalkboard talk with one presenter. The lectures will be held outside Marks Annex. The time/day may change based on the weather but will usually be Thursdays, 4:30-5:30pm. If you'd like to be added to the e-mail list, please let Ben know.
Pantelis Vafidis, "Intro to Transformers", June 2023
Summer 2024 Schedule
| Day | Time | Presenter | Topic | Difficulty |
|---|---|---|---|---|
| Thurs June 6 | 4:30-5:30pm | Ben Cowley | Bayesian Active Learning | intermediate |
| Thurs June 13 | 4:30-5:30pm | Wolf de Wulf | Gaussian Processes | intermediate |
| Thurs June 20 | 4:30-5:30pm | Ryan Fayyazi | Sequential Monte Carlo | Intermediate |
| Thurs June 27 | 4:30-5:30pm | Tig Moore | Pruning in biological and artificial neural networks | Beginner |
| Thurs July 4 | -- | No meeting | -- | -- |
| Thurs July 11 | 4:30-5:30pm | Ludovic Corcos | Physics-Informed Neural Networks | Advanced |
| Thurs July 18 | 4:30-5:30pm | Satwik Pasani | Maximum Entropy Models | Intermediate |
| Thurs July 25 | 4:30-5:30pm | Todd Morrill | Variational Autoencoders | Intermediate |
| Thurs Aug 1 | 4:30-5:30pm | CiCi Zheng | Predictive coding 101 | beginner |
| Thurs Aug 8 | 4:30-5:30pm | Christos Kaneen | Bio-inspired credit assignment | Intermediate |
| Thurs Aug 15 | 4:30-5:30pm | Arkarup Banerjee | Computing time in the Brain | Beginner |
| Thurs Aug 22 | 4:30-5:30pm | Jamie Lohoff | Automatic Differentiation 101 | Beginner |
| Thurs Aug 29 | 4:30-5:30pm | Kyle Daruwalla | Derivatives, Descent, and (automatic) Differentiation | Intermediate |
| Thurs Sep 5 | 4:30-5:30pm | Ari Benjamin | Stochastic Gradient Estimation | Beginner |
| Thurs Sep 12 | 4:30-5:30pm | Masayuki (Moon) Nagai | Kolmogorov-Arnold Networks (KANs) | Beginner |
| Thurs Sep 19 | 4:30-5:30pm | Christian Pehle | Spikes, States and Spaces | Advanced |
| Thurs Oct 3 | 4:30-5:30pm | Tingkai Liu | Transformers and Mamba | advanced |
beginner: No formal background in computational approaches but motivated to learn.
intermediate: Some knowledge in linear algebra, statistics, and/or computer science.
advanced: Could be a reviewer for an ML conference paper.
(old) Summer 2023 Schedule
| Day | Time | Presenter | Topic | Difficulty |
|---|---|---|---|---|
| Thurs June 8 | 5-6pm | Ben Cowley | Linear regression with active learning | intermediate |
| Tues June 13 | 5-6pm | Pantelis Vafeidis | Introduction to Transformers | intermediate |
| Fri June 30 | 4-5pm | Kyle Daruwalla | Double Descent in Deep Learning | intermediate |
| Wed July 5 | 5-6pm | Ryan Fayyazi | Diffusion models: Different perspectives | intermediate |
| Tues July 11 | 5-6pm | Xiaoxuan Lei | Introduction to Topological Data Analysis | intermediate |
| Tues July 25 | 5-6pm | Christian Pehle | Optimal Control Theory | advanced |
| Tues Aug 1 | 5-6pm | Arkarup Banerjee | Coincidence detectors | neuroscience |
| Tues Aug 8 | 5-6pm | Burak Gurbuz | Introduction to Continual Learning | Beginner |
| Thurs Aug 17 | 4:30-5:30pm | Ben Cowley | The History of Optimization | intermediate |
| Tues Aug 22 | 4:30-5:30pm | Ari Benjamin | The dynamics of gradient descent | intermediate |
| Tues Aug 29 | 4:30-5:30pm | CiCi Zheng | Hopfield networks and energy functions | beginner |