most citedGaussian Variational Inference with Non-Gaussian Factors for State Estimation: A UWB Localization Case Study

1 citations · 1 across the 3 of their papers we have counts for

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5 papers

cs.RO20261 cited

Gaussian Variational Inference with Non-Gaussian Factors for State Estimation: A UWB Localization Case Study

Andrew Stirling, Mykola Lukashchuk, Dmitry Bagaev +2

This letter extends the exactly sparse Gaussian variational inference (ESGVI) algorithm for state estimation in two complementary directions. First, ESGVI is generalized to operate…

cs.AI2025

Active Inference is a Subtype of Variational Inference

Wouter W. L. Nuijten, Mykola Lukashchuk

Automated decision-making under uncertainty requires balancing exploitation and exploration. Classical methods treat these separately using heuristics, while Active Inference unifi…

math.ST2025

Resolution of the Borel-Kolmogorov Paradox via the Maximum Entropy Principle

Raphaël Trésor, Mykola Lukashchuk

This paper presents a rigorous resolution of the Borel-Kolmogorov paradox using the Maximum Entropy Principle. We construct a metric-based framework for Bayesian inference that uni…

cs.LG2025

GateTS: Versatile and Efficient Forecasting via Attention-Inspired routed Mixture-of-Experts

Kyrylo Yemets, Mykola Lukashchuk, Ivan Izonin

Accurate univariate forecasting remains a pressing need in real-world systems, such as energy markets, hydrology, retail demand, and IoT monitoring, where signals are often intermi…

stat.ML2025

Expected Free Energy-based Planning as Variational Inference

Bert de Vries, Wouter Nuijten, Thijs van de Laar +13

We address the problem of planning under uncertainty, where an agent must choose actions that not only achieve desired outcomes but also reduce uncertainty. Traditional methods oft…