1. Lectures
  2. Important Dates

Lectures

The slides and resources for each lecture will be updated after the class. The schedule below is tentative and both the order and the content will almost definitely change as the semester goes along.

Date Lecture
19-Aug Introduction
21-Aug Neural networks refresher
26-Aug Symbolic logic
28-Aug Logic (continued)
2-Sep Neuro-symbolic methods: Overview
4-Sep Neuro-symbolic methods (continued)
9-Sep Neuro-symbolic methods (continued)
11-Sep Logic as loss: Overview
16-Sep Semantic loss
18-Sep Semantic loss (continued)
23-Sep Multi-valued logic and t-norm losses
25-Sep T-norm losses (continued)
30-Sep Buffer lecture
2-Oct Buffer lecture
7-Oct Fall break, no class
9-Oct Fall break, no class
14-Oct Using knowledge to design models
16-Oct (continued)
21-Oct Reasoning about model predictions, structured prediction
23-Oct (continued)
28-Oct Graph search for structures
30-Oct Integer linear programming inference
4-Nov Training with inference
6-Nov Test-time compute with LLMs
11-Nov Training with symbols within networks
13-Nov The straight-through estimator
18-Nov Gumbel softmax
20-Nov Reinforcement learning
25-Nov Buffer lecture
27-Nov Thanksgiving, no class
2-Dec Buffer lecture
4-Dec Looking back at the semester

Important dates

Date Deadline
9-Sep Project team information due
18-Sep Review 1 due
30-Sep Project proposals due
28-Oct Project intermediate status report due
29-Oct Review 2 due
20-Nov Review 3 due
4-Dec Project final report due