Publications

Lazzerini, Alejandra Avalos-Pacheco, Monia Lupparelli, Francesco C. Stingo (2023). Bayesian inference of multiple Ising models for heterogeneous data. In EcoSta2023.

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Ranciati, Alberto Roverato (2023). On the application of Gaussian graphical models to paired data problems. arXiv.

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Francesco C. Stingo (2023). Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure. In EMS2023.

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Alejandra Avalos-Pacheco (2023). Bayesian Inference of Multiple Ising Models for Heterogeneous Data. In Bayes Comp 2023.

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Alberto Roverato, Dung Ngoc Nguyen (2023). Exploration of the search space of Gaussian graphical models for paired data. arXiv.

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Ni, Francesco C. Stingo, Baladandayuthapani (2022). Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure. Journal of Machine Learning Research, 23(1-29).

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Gianluca Sottile, Luigi Augugliaro, Veronica Vinciotti, Arancio, Coronnello (2022). Sparse inference of the human hematopoietic system from heterogeneous and partially observed genomic data. arXiv.

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Gianluca Sottile, Luigi Augugliaro, Veronica Vinciotti, W. Arancio, C. Coronnello (2022). Sparse inference of the human hematopoietic system from heterogeneous and partially observed genomic data. In Workshop.

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Gianluca Sottile, Luigi Augugliaro, Veronica Vinciotti, Arancio, Coronnello (2022). Sparse inference of the human hematopoietic system from heterogeneous and partially observed genomic data. In Workshop.

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Monia Lupparelli, G.M. Marchetti (2022). Path-dependent parametric decompositions in Ising models. In Workshop.

C. Busatto, Francesco C. Stingo (2022). Multiple graphical models with horseshoe. In Workshop.

Antonino Abbruzzo, N. Argentino, R. Mohammadi, M. De Iorio, W. van den Boom, A. Beskos (2022). MCMC sampling for Bayesian Gaussian structural learning. In Workshop.

Ranciati, Alberto Roverato (2022). Learning Gaussian graphical models for paired data with the pdglasso. In Workshop.

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Veronica Vinciotti, A. Polinelli, E. Wit (2022). Causal glms within a graphical modelling framework. In Workshop.

Guido Consonni, Federico Castelletti (2022). Bayesian sample size determination for causal discovery. In Workshop.

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Federico Castelletti, L. Ferrini (2022). Bayesian nonparametric mixtures of directed acyclic graphs for heterogeneous causal inference. In Workshop.

Peterson, Francesco C. Stingo (2021). Bayesian Estimation of Single and Multiple Graphs. Chapman and Hall/CRC, ch. 14(327-348).

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Ni, Baladandayuthapani, Vannucci, Francesco C. Stingo (2021). Bayesian graphical models for modern biological applications. Statistical Methods & Applications, 31(197-225).

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