In the previous blog we introduced diffusion model (DDPM) which is to learn the step (time \(t\)) and the noise function (NN model) by adding Gaussian noise to an image step by step and reversing the process by denosiing from Gaussian noise to an image. Diffusion model is the most …

The previous notes introduced the text generation models (GPT family). This reading note is about image generator papers.

Similar to text generator which generate the next token, OpenAI has image-GPT which is a large transformer trained on next pixel prediction in which the pixels are concated into a vector to …

1. GPT-1

Improving Language Understandingby Generative Pre-Training

What the problem GPT-1 solve?

Before GPT-1, NLP was usually a supervised model. For each task, there are some labeled data, and then develop a suoervised model based on these labeled data. There are several problems with this approach: First, labeled data is …

multi-armed bandit and how to use it in CTR optimization

paper reading and summary

Recommendation system introduction - collaborative filtering, DNN for query and item embedding