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cs.LG2026
Information Geometry of Message Passing
Mykola Lukashchuk, Kyrylo Yemets, Alex Ledbetter +1
We show that the natural-gradient stationary condition of variational inference has an edge-local form on a Forney-style factor graph. We start from the Bethe free energy and const…
cs.LG2026
A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression
Wouter W. L. Nuijten, Esther G. van Pelt, Albert Podusenko +2
Multi-output Gaussian process regression scales cubically in the number of observations times outputs, and dense kernel-matrix methods need bespoke handling whenever different outp…
cs.LG2026
Composing Non-Conjugate Factor Graphs with Closed-Form Variational Inference
Mykola Lukashchuk, Kyrylo Yemets, Wouter M. Kouw +4
Stacking probabilistic building blocks into deeper architectures typically breaks closed-form inference. We show that closed-form inference can be preserved. We identify five facto…