activity
20242026
collaborators

5 papers

cs.CL2026

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…

stat.ME2026

A General Approach to Visualizing Uncertainty in Statistical Graphics

Bernarda Petek, David Nabergoj, Erik Å trumbelj

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

Reducing normalizing flow complexity for MCMC preconditioning

David Nabergoj, Erik Å trumbelj

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

Empirical evaluation of normalizing flows in Markov Chain Monte Carlo

David Nabergoj, Erik Å trumbelj

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…

stat.ML2024

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…