11 citations · 28 across the 12 of their papers we have counts for
4 papers · 1 filter
Discrete Bayesian Sample Inference for Graph Generation
Ole Petersen, Marcel Kollovieh, Marten Lienen +1
Generating graph-structured data is crucial in applications such as molecular generation, knowledge graphs, and network analysis. However, their discrete, unordered nature makes th…
Edit-Based Flow Matching for Temporal Point Processes
David Lüdke, Marten Lienen, Marcel Kollovieh +1
Temporal point processes (TPPs) are a fundamental tool for modeling event sequences in continuous time, but most existing approaches rely on autoregressive parameterizations that a…
UnHiPPO: Uncertainty-aware Initialization for State Space Models
Marten Lienen, Abdullah Saydemir, Stephan Günnemann
State space models are emerging as a dominant model class for sequence problems with many relying on the HiPPO framework to initialize their dynamics. However, HiPPO fundamentally…
Generative Modeling with Bayesian Sample Inference
Marten Lienen, Marcel Kollovieh, Stephan Günnemann
We present a novel view of diffusion-like generative modeling from the perspective of iterative Gaussian posterior inference. By treating the generated sample as an unknown variabl…