CountsDiff: A Diffusion Model on the Natural Numbers for Generation and Imputation of Count-Based Data

1. 1Understand the limitations of existing diffusion models for discrete ordinal data
2. 2Apply CountsDiff to model distributions on natural numbers using a survival probability schedule
3. 3Implement CountsDiff for generation and imputation of count-based data
4. 4Evaluate the performance of CountsDiff on specific tasks and datasets

Data scientists and AI researchers working with count-based data can benefit from CountsDiff for generative tasks, while software engineers can apply it to real-world problems

💡 CountsDiff extends the Blackout diffusion framework for discrete ordinal data

📊 New diffusion model CountsDiff generates & imputes count-based data on natural numbers!