activity
20242026
most citedBenchmarking the Fidelity and Utility of Synthetic Relational Data

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CY2026

A Scoping Review of the Negative Effects of Digital Technology on Cognition

Urška Žnidarič, Erik Štrumbelj, Octavian Machidon

The rapid integration of digital technology into daily life has prompted sustained concern regarding its impact on human cognition. To characterize documented negative effects and…

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…

stat.ME2025

A General Approach to Visualizing Uncertainty in Statistical Graphics

Bernarda Petek, David Nabergoj, Erik Štrumbelj

We present a general approach to visualizing uncertainty in static 2-D statistical graphics. If we treat a visualization as a function of its underlying quantities, uncertainty in…

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…

cs.DB2024★ 1 cited

Benchmarking the Fidelity and Utility of Synthetic Relational Data

Valter Hudovernik, Martin Jurkovič, Erik Štrumbelj

Synthesizing relational data has started to receive more attention from researchers, practitioners, and industry. The task is more difficult than synthesizing a single table due to…