Russo's formula for random interlacements
Diego F. de Bernardini, Serguei Popov

TL;DR
This paper derives explicit formulas for how the probability of increasing events in the random interlacements model changes with the model's intensity parameter, providing insights into the model's sensitivity.
Contribution
It introduces explicit expressions for the derivative of increasing event probabilities in the random interlacements model with respect to intensity.
Findings
Derived explicit formulas for probability derivatives
Applied formulas to finite subsets of the lattice
Enhanced understanding of model sensitivity to parameters
Abstract
In this paper we obtain a couple of explicit expressions for the derivative of the probability of an increasing event in the random interlacements model. The event is supported in a finite subset of the lattice, and the derivative is with respect to the intensity parameter of the model.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
