Date	Lecture	Info
Introduction and background
8/14	Introduction and overview [slides]
8/15	Data and dimensionality [slides] [whiteboard]	References: High dim space (CMU lecture) Foundations of Data Science, Chapter 1
Data representation space and structures
8/20	Dimension reduction, metric learning, PCA, MDS [Linear transforms and basis] [PCA and MDS]
8/21	Deep learning workflow and useful programming tools [Notebook (zip)]
8/22	Structures in data spaces, manifolds, subspaces, sparse coding [slides]
Visual representations
8/27	Pixels, 3D points, and cameras [slides]
8/28	Image operations
8/29	Semantics
9/3	Videos
9/4	Project and research discussion, how to do research?
9/5	Image subspaces and manipulations
Language representations
9/10	Representing words and sentences
9/11	Project and research discussion, how to read a paper?
9/12	Language model pretraining
9/17	NLP tasks
9/18	Project and research discussion, how to write a paper?
9/19	Zero-shot and in-context learning
Audio representations
9/24	Representing sound
9/25	Project and research discussion
9/26	Audio generation and editing
Graphs
10/1	Graphs and neural networks
10/2	Project and research discussion
10/3	GNN applications
Multi-modal representations
10/8	Midterm
10/9	Project and research discussion
10/10	Overview of multi-modal learning
10/15	Multimodal representation alignment
10/16	Project and research discussion
10/17	Multimodal reasoning
Advanced Topics -- Implicit representations
10/22	Implicit Neural Reprsentations	References: Implicit Neural Representations with Periodic Activation Functions NeRF
10/23	Project and research discussion
10/24	Deep implicit layers	References: NeurIPS 2020 tutorial
Advanced Topics -- Meta-learning and domain adaptation
10/29	Meta-learning	References: Meta-Learning in Neural Networks A Survey Meta Learning - AAAI 2021 tutorial
10/30	Project and research discussion
10/31	Domain adaptation, transfer learning, life-long learning	References: Domain Generalization A Survey A Comprehensive Survey on Transfer Learning A Comprehensive Survey of Continual Learning Theory, Method and Application
Advanced Topics -- Unsupervised and self-supervised learning
11/5	Unsupervised learning and discovery	References: UFLDL Tutorial Tutorial on Variational Autoencoders Semi-Supervised and Unsupervised Deep Visual Learning A Survey
11/6	Project and research discussion
11/7	Self-supervised learning	References: CS231n lecture 12 DINO DINO v2
Advanced Topics -- Beyond perception
11/12	AI Agent
11/13	Project and research discussion
11/14	Embodied intelligence	References: CVPR 2022 workshop
Final project presentations
11/19	Class review and discussion
11/20	Group presentations 1	References: Group 1, 2
11/21	Group presentations 2	References: Group 3, 4, 5
11/26	Group presentations 3	References: Group 6, 7, 8
11/27	No class (Thanksgiving)
11/28	No class (Thanksgiving)
12/3	No class (Friday Class Schedule)