15: High-Resolution Image Synthesis with Latent Diffusion Models (
Latent Diffusion Model
)
About
📝 100 AI Papers with Code
About this series
Transformer
Vision Transformer
🎓 Stanford CS336: LLM from Scratch
About this course
Lecture 01: Introduction & BPE
Lecture 02: PyTorch Basics & Resource Accounts
Lecture 03: Transformer LM Architecture
Lecture 04: MoE Architecture
Lecture 05&06: GPU Optimization, Triton & FlashAttention
Lecture 07&08: Parallelism
Lecture 09&11: Scaling Laws
Lecture 10: Inference & Deployment
Lecture 12: Evaluation
Lecture 13&14: Data Collection & Processing
Lecture 15: LLM Alignment SFT & RLHF(PPO, DPO)
Lecture 16 & 17: LLM Alignment SFT & RLVR(GRPO)
Assignment 01: BPE Tokenizer & Transformer LM
Assignment 02: Flash Attention & Parallelism
Assignment 05: SFT & GRPO
📖 Deep Learning Foundation & Concepts
About this book
On this page
1
Latent Diffusion Model
1.1
Experiment
2
Summary
3
Key Concepts
4
Q & A
5
Related resource & Further Reading
15: High-Resolution Image Synthesis with Latent Diffusion Models (
Latent Diffusion Model
)
Generative Model
一种在低维潜在空间中进行扩散建模的生成方法,在显著降低计算成本的同时,实现高分辨率、高质量的图像生成。
# Preliminary
1
Latent Diffusion Model
1.1
Experiment
2
Summary
3
Key Concepts
4
Q & A
5
Related resource & Further Reading
Back to top