Mattis Hartwig — accepted AI-conference papers

2026

Integrating Atmospheric Dispersion Modeling Priors into Cuboid Splatting for Spatiotemporal Reconstruction of Airborne Radioiodine After Nuclear Accidents

Mareike Böckel, Stephan Doerfel, Kathrin Meisenberg, Oliver Meisenberg, Max Friedrich, Mattis Hartwig

IJCAI 2026

In nuclear power plant accidents, airborne radioiodine poses major health risks, making reliable reconstructions of its spatiotemporal distribution crucial for emergency management. Current state-of-the-art prognosis systems use atmospheric dispersion modeling but ignore posterior evidence from emer

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2025

Approximate Lifted Model Construction

Malte Luttermann, Jan Speller, Marcel Gehrke, Tanya Braun, Ralf Möller, Mattis Hartwig

IJCAI 2025

Probabilistic relational models such as parametric factor graphs enable efficient (lifted) inference by exploiting the indistinguishability of objects. In lifted inference, a representative of indistinguishable objects is used for computations. To obtain a relational (i.e., lifted) representation, t

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2021

Handling Overlaps When Lifting Gaussian Bayesian Networks

Mattis Hartwig, Tanya Braun, Ralf Möller

IJCAI 2021poster

Gaussian Bayesian networks are widely used for modeling the behavior of continuous random variables. Lifting exploits symmetries when dealing with large numbers of isomorphic random variables. It provides a more compact representation for more efficient query answering by encoding the symmetries usi…

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