Evidence of Replica Symmetry Breaking under the Nishimori conditions in epidemic inference on graphs
Alfredo Braunstein, Louise Budzynski, Matteo Mariani, Federico Ricci-Tersenghi

TL;DR
This paper demonstrates that replica symmetry breaking can occur under Nishimori conditions in epidemic inference models, challenging the assumption that these conditions guarantee replica symmetry, with implications for inference accuracy.
Contribution
The paper provides the first counter-example showing replica symmetry breaking under Nishimori conditions in epidemic inference, using a geometrical model and cavity method analysis.
Findings
Evidence of replica symmetry breaking under Nishimori conditions
Correlated disorder in epidemic models causes symmetry breaking
Implications for inference methods in epidemic modeling
Abstract
In Bayesian inference, computing the posterior distribution from the data is typically a non-trivial problem, which usually requires approximations such as mean-field approaches or numerical methods, like the Monte Carlo Markov Chain. Being a high-dimensional distribution over a set of correlated variables, the posterior distribution can undergo the notorious replica symmetry breaking transition. When it happens, several mean-field methods and virtually every Monte Carlo scheme can not provide a reasonable approximation to the posterior and its marginals. Replica symmetry is believed to be guaranteed whenever the data is generated with known prior and likelihood distributions, namely under the so-called Nishimori conditions. In this paper, we break this belief, by providing a counter-example showing that, under the Nishimori conditions, replica symmetry breaking arises. Introducing a…
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Taxonomy
TopicsData-Driven Disease Surveillance · RNA and protein synthesis mechanisms · Fractal and DNA sequence analysis
MethodsSparse Evolutionary Training
