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cs.LG2026
On architectural choices for interpretability and thermodynamic consistency in Physically Recurrent Neural Networks in the low-data regime
M. A. Maia, K. A. Meyer, A. M. C. M. van Gils +2
In this paper, we unravel the effect of different decoder architectures on the interpretability of the latent space of the Physically Recurrent Neural Network. Particular emphasis…
stat.CO2026
Piecewise Deterministic Markov Processes for Bayesian Inference of PDE Coefficients
Leon Riccius, Iuri B. C. M. Rocha, Joris Bierkens +2
We develop a general framework for piecewise deterministic Markov process (PDMP) samplers that enables efficient Bayesian inference in non-linear inverse problems with expensive li…