69 citations · 73 across the 7 of their papers we have counts for
8 papers
Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical Analysis
Muhammad Rizwan, David Nabergoj, Jure Demšar
Background: Depression frequently co-occurs with ADHD and autism spectrum disorder (ASD), but population-level differences in symptom expression between these groups remain underex…
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…
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…
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…
Control, Transport and Sampling: Towards Better Loss Design
Qijia Jiang, David Nabergoj
Leveraging connections between diffusion-based sampling, optimal transport, and stochastic optimal control through their shared links to the Schrödinger bridge problem, we propose…
pocoMC: A Python package for accelerated Bayesian inference in astronomy and cosmology
Minas Karamanis, David Nabergoj, Florian Beutler +2
pocoMC is a Python package for accelerated Bayesian inference in astronomy and cosmology. The code is designed to sample efficiently from posterior distributions with non-trivial g…
Accelerating astronomical and cosmological inference with Preconditioned Monte Carlo
Minas Karamanis, Florian Beutler, John A. Peacock +2
We introduce Preconditioned Monte Carlo (PMC), a novel Monte Carlo method for Bayesian inference that facilitates efficient sampling of probability distributions with non-trivial g…
Predicting the Popularity of Games on Steam
Andraž De Luisa, Jan Hartman, David Nabergoj +5
The video game industry has seen rapid growth over the last decade. Thousands of video games are released and played by millions of people every year, creating a large community of…