Schedule

Readings:

• “Deep Learning” by Yann LeCun, Yoshua Bengio and Geoffrey Hinton (use BU institutional login to access)
• Understanding Deep Learning, Chapter 1

Readings:

• Understanding Deep Learning, Chapter 2

Readings:

• Understanding Deep Learning, Chapter 3

Readings:

• Understanding Deep Learning, Chapter 4

Readings:

• Understanding Deep Learning, Chapter 5

Readings:

• Understanding Deep Learning, Chapter 6

Readings:

• Understanding Deep Learning, Chapter 7

Readings:

• Understanding Deep Learning, Chapter 8

Readings:

• Understanding Deep Learning, Chapter 9
• For Valid Generalization the Size of the Weights is More Important than the Size of the Network
• Train faster, generalize better: Stability of stochastic gradient descent

Readings:

• Understanding Deep Learning, Chapter 10

Readings:

• Understanding Deep Learning, Chapter 11

Readings:

• n/a

Please bring a laptop that you can work on.

Readings:

• The Unreasonable Effectiveness of Recurrent Neural Networks

Readings:

• Understanding Deep Learning, Chapter 12
• Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention)
• The Illustrated Transformer

Readings:

• Understanding Deep Learning, Chapter 12
• The Illustrated Transformer
• Andrej Karpathy lecture notes re: LLM tokenization

Readings:

• Image GPT
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Scaling Vision Transformers
• Learning Transferable Visual Models From Natural Language Supervision
• Masked Autoencoders are Scalable Vision Learners (tutorial)
• Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
• Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

Readings:

• Signature Verification using a “Siamese” Time Delay Neural Network
• Learning a similarity metric discriminatively, with application to face verification
• Learning Transferable Visual Models From Natural Language Supervision

Readings:

• Many links in the slides

Readings:

• Understanding Deep Learning, Chapter 15
• Many paper links in the slides

Readings:

• Understanding Deep Learning, Chapters 14+17

Readings:

• Understanding Deep Learning, Chapter 16

Readings:

• Understanding Deep Learning, Chapter 18
• What are Diffusion Models?

Readings:

• Neural Fields in Visual Computing and Beyond
• Many links in the slides

Readings:

• Understanding Deep Learning, Chapter 19
• RLHF: Reinforcement Learning from Human Feedback

Readings:

• TBD

Students will present their final projects.