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cs.LG2025
Reducing normalizing flow complexity for MCMC preconditioning
David Nabergoj, Erik Štrumbelj
Preconditioning is a key component of MCMC algorithms that improves sampling efficiency by facilitating exploration of geometrically complex target distributions through an inverti…
cs.LG2025
RelDiff: Relational Data Generative Modeling with Graph-Based Diffusion Models
Valter Hudovernik, Minkai Xu, Juntong Shi +4
Real-world databases are predominantly relational, comprising multiple interlinked tables that contain complex structural and statistical dependencies. Learning generative models o…
cs.LG2024
Empirical evaluation of normalizing flows in Markov Chain Monte Carlo
David Nabergoj, Erik Štrumbelj
Recent advances in MCMC use normalizing flows to precondition target distributions and enable jumps to distant regions. However, there is currently no systematic comparison of diff…