1 citations · 1 across the 13 of their papers we have counts for
3 papers · 1 filter
Decafs: Disentangled Conditional adversarial Flows
Anirudh jain, Sakshi Varshney, Samuel Kaski +1
Flow-based models have established state-of-the-art performance in generative modeling across domains, but are hard to interpret due to their complex latent embeddings. In particul…
Divide-and-Denoise: A Game-Theoretic Method for Fairly Composing Diffusion Models
Abhi Gupta, Polina Barabanshchikova, Vikas Garg +2
The abundance of pre-trained diffusion models provides an opportunity for composition. Combining several models, however, runs the risk of one model dominating or models disagreein…
A Theory of Random Graph Shift in Truncated-Spectrum vRKHS
Zhang Wan, Tingting Mu, Samuel Kaski
This paper develops a theory of graph classification under domain shift through a random-graph generative lens, where we consider intra-class graphs sharing the same random graph m…