Class Schedule

This page will be filled with more details as the topic talks and project talks are scheduled. Click on the title for more details, including reading assignments, descriptions of homework assignments, etc.

Date Topic Assignment
Aug 24 Intro to Neural Nets
Aug 31 Backpropagation Personal ads due.
Deep Learning Homework 1 (COVID-19 Prediction) assigned.
Sep 07 Reinforcement Learning
Evolutionary Computation
Sep 14 Neuroevolution Homework 1 (DL/Backpropagation) due.
Decision Making Homework 2 (COVID-19 Prescription) assigned.
Sep 21 Self-Organizing Maps
Computational Neuroscience
Sep 28 Brain Organization Homework 2 (RL/Neuroevolution) due.
Cognitive Modeling Topic talk proposals due.
Oct 05 Exam Practice questions; Exam Feedback
Oct 12 Models of Biological Lifelong learning (Logan, Margaret, Marlan)
Computational modeling of the visual system (Jasmeet, PK)
Oct 19 Transformer architectures (Shuozhe, Zac)
Diffusion models (Jeremiah, Michael)
Oct 26 9amNeurosymbolic systems (Amitayush)
     10:30am Physics-based neural networks (Christopher, Sebastian)
      1:30pm Neural architecture search (Jahnavi, Jordan)
Nov 02 Video understanding (Alex, Carlos) Project proposals due
Neural networks in personalized medicine (Chloe, Cole)
Nov 09 Integrating social media data into stock market prediction (Kyle, Marco, Shreya)
Continual reinforcement learning for stock market prediction (Guan, Roberto)
Nov 16 Open-ended evolution of behavior (David, Matthew)
Fairness and bias in neural networks (Amit, Nikhil, Priyal)
Nov 30Project talks & Class Evaluation (in person, GDC 6.302)
9:00 Logan, Margaret, Marlan: Biologically motivated continuous learning
9:15 Jasmeet, PK: Robust visual processing with a V1 model
9:30 Alex, Carlos: Improving video processing architectures
9:45 Shuozhe, Zac: Prediting time series with transformers
10:00 Amitayush: Program synthesis from natural language with limited corpora
10:15 Coffee break
10:30 Jordan, Jahnavi: NAS for diffusion models
10:45 Jeremiah, Michael: Font diffusion
11:00 Kyle, Marco, Shreya: Stock prediction based on social media sentiment
11:15 Guan, Roberto: Continual reinforcement learning for stock market prediction
11:30 Lunch break
1:30 Chloe, Cole: Categorizing COVID Patients
1:45 Chris, Sebastian: Physics-based NN on seismic fullwave inversion
2:00 David, Matthew: Co-evolving game agents and environments
2:15 Amit, Nikhil, Priyal: De-biasing news articles/Mitigating sensitive attribute leakage
2:30 Class Evaluation
Dec 13 Project papers due.
8am CST
Wed Nov 9 22:50:57 CST 2022