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stat.ML2026
Conditioning Gaussian Processes on Almost Anything
Henry Moss, Lachlan Astfalck, Thomas Cowperthwaite +5
Gaussian processes (GPs) offer a principled probabilistic model over functions, but exact inference is restricted to the linear-Gaussian regime. We establish an explicit equivalenc…
stat.ML2026
Hypergraph Generation via Structured Stochastic Diffusion
Christopher Nemeth
Hypergraphs model higher-order interactions, but realistic hypergraph generation remains difficult because incidence, hyperedge-size heterogeneity, and overlap structure are not fa…
stat.ML2026
Generator-based Graph Generation via Heat Diffusion
Anthony Stephenson, Ian Gallagher, Christopher Nemeth
Graph generative modelling has become an essential task due to the wide range of applications in chemistry, biology, social networks, and knowledge representation. In this work, we…