Schedule for In-class Presentations

Date	Topic	Suggested Readings	Reference	Homework
Aug. 25	Introduction [En] Mathematics [En] Machine Learning Basics [En]	Deep Learning Book Chap. 2 Chap. 3 Chap. 5
Sep. 8	Feedforward Neural Networks & Optimization Tricks [En]	Deep Learning Book Chap. 6 Chap. 7 Chap. 8
Sep. 15	Introduction to Pytorch [En] PyTorch part 1 PyTorch Part 2	Python Numpy Tutorial Neural Network from Scratch Dive into Deep Learning		HW1 [En]
Sep. 22	Convolutional Neural Networks & Recurrent Neural Networks	Deep Learning Book Chap. 9 Chap. 10	ResNet GRU DenseNet
Sep. 29	Word Representation Learning	Word2Vec	GloVe SGNS
Oct. 6	Attention, Transformers	The annotated Transformer (blog) Transformer Rotary Position Embedding	Relative Position Embedding RoBERTa ViT Reformer FlashAttention
Oct. 15	No class (Project proposal). Project instruction [En]			HW2 (to be announced)
Nov. 3	Large Language Models I	BERT GPT-1 GPT-3 LoRA Scaling Law GPT in 60 Lines of NumPy	XLNet UL2 OPT PaLM LLaMA Survey of Pre-trained LMs
Nov. 10	Large Language Models II - Prompt Tuning	Chain-of-Thought Prompt Engineering (Blog by Lilian Weng)	Prefix-Tuning Promtp Tuning LoRA Instruction Tuning InstructGPT Automatic Prompt Engineer
Nov. 17	Generative Models	GAN VAE Evidence Lower Bound ELBO — What & Why (Blog) Diffusion Probabilistic Model	beta-VAE CycleGAN Latent Diffusion Stable diffusion
Nov. 24	Graph Representation Learning	GCN Graph Neural Networks Implementation Tutorial	DeepWalk LINE GIN Open Graph Benchmark
Dec. 1	Poster Session