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Nathaniel Lee Diamant

2 accepted papers

2024

Feedback Efficient Online Fine-Tuning of Diffusion Models

ICML 2024poster

Diffusion models excel at modeling complex data distributions, including those of images, proteins, and small molecules. However, in many cases, our goal is to model parts of the distribution that maximize certain properties: for example, we may want to generate images with high aesthetic quality, o…

Cited by 26SourcePDFScholar
2023

Improving Graph Generation by Restricting Graph Bandwidth

ICML 2023poster

Deep graph generative modeling has proven capable of learning the distribution of complex, multi-scale structures characterizing real-world graphs. However, one of the main limitations of existing methods is their large output space, which limits generation scalability and hinders accurate modeling…