3 papers
cs.AI2025
Approximate Lifted Model Construction
Malte Luttermann, Jan Speller, Marcel Gehrke +3
Probabilistic relational models such as parametric factor graphs enable efficient (lifted) inference by exploiting the indistinguishability of objects. In lifted inference, a repre…
cs.AI2024
Estimating Causal Effects in Partially Directed Parametric Causal Factor Graphs
Malte Luttermann, Tanya Braun, Ralf Möller +1
Lifting uses a representative of indistinguishable individuals to exploit symmetries in probabilistic relational models, denoted as parametric factor graphs, to speed up inference…
cs.AI2021
Lifting DecPOMDPs for Nanoscale Systems -- A Work in Progress
Tanya Braun, Stefan Fischer, Florian Lau +1
DNA-based nanonetworks have a wide range of promising use cases, especially in the field of medicine. With a large set of agents, a partially observable stochastic environment, and…