Course:CPSC522/Index

A

• Artificial General Intelligence
• Learning Attention via Active Inference

B

• Bayesian Coresets
• Bayesian Networks
• Bounded Rationality
• Bayesian Optimization

D

• Decision Trees
• Dynamic Bayesian Networks

E

• Elicitation of Factored Utilities
• Exploring Results of Conditional Generative Adversarial Networks with Self-Organizing Maps

G

• Game Theory
• Graphical Models

H

• Hierarchical Control
• Hidden Markov Models

I

• Is Attention Explanation?

K

• Knowledge Graphs

L

• Logic Programming
• Long Short-Term Memory Networks (LSTMs)

M

• Markov Decision Process
• Markov Logic
• Markov Networks
• Markov Chain Monte Carlo
• Matrix Factorization For Recommender Systems

N

• Neural Network

O

• Ontology
• Online Pattern Analysis by Evolving Self-organizing Maps

P

• Probability
• Probability - general semantics
• Predicate Calculus
• Particle Filtering

R

• Recurrent Neural Networks
• Reinforcement Learning
• Reinforcement Learning with Function Approximation

S

• Sequential Monte Carlo for Probabilistic Graphical Models
• Support Vector Machines
• Stacked Generative Adversarial Networks
• Self-Organizing Maps
• Scaling Memory for Transformers

T

• Temporal Difference
• Text Summarization using Machine Learning

V

• Value of Information
• Variable Elimination