Manuele Leonelli

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 37

Top Topics

Probabilistic Graphical Models

Sensitivity Analysis

Bayesian Networks

Structural Learning

Top Venues

Int. J. Approx. Reason.

Knowl. Based Syst.

Publications

Rafael Ballester-Ripoll, Manuele Leonelli
Global Sensitivity Analysis of Uncertain Parameters in Bayesian Networks. CoRR (2024)
Manuele Leonelli, Gherardo Varando
Context-Specific Refinements of Bayesian Network Classifiers. CoRR (2024)
Manuele Leonelli, Gherardo Varando
Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear. Appl. Intell. 54 (2) (2024)
Manuele Leonelli, Gherardo Varando
Structural learning of simple staged trees. Data Min. Knowl. Discov. 38 (3) (2024)
Manuele Leonelli, Jim Q. Smith, Sophia K. Wright
The diameter of a stochastic matrix: A new measure for sensitivity analysis in Bayesian networks. CoRR (2024)
Jack Storror Carter, Manuele Leonelli, Eva Riccomagno, Gherardo Varando
Learning Staged Trees from Incomplete Data. CoRR (2024)
Manuele Leonelli, Ramsiya Ramanathan, Rachel L. Wilkerson
Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package. Knowl. Based Syst. 278 (2023)
Manuele Leonelli, Gherardo Varando
Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear. CoRR (2023)
Fabio Crimaldi, Manuele Leonelli
AI and the creative realm: A short review of current and future applications. CoRR (2023)
Rafael Ballester-Ripoll, Manuele Leonelli
The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks. CoRR (2023)
Rafael Ballester-Ripoll, Manuele Leonelli
The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks. Int. J. Approx. Reason. 159 (2023)
Manuele Leonelli, Gherardo Varando
Context-Specific Causal Discovery for Categorical Data Using Staged Trees. AISTATS (2023)
Federico Carli, Manuele Leonelli, Gherardo Varando
A new class of generative classifiers based on staged tree models. Knowl. Based Syst. 268 (2023)
Manuele Leonelli, Gherardo Varando
Structural Learning of Simple Staged Trees. CoRR (2022)
Rafael Ballester-Ripoll, Manuele Leonelli
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks. PGM (2022)
Manuele Leonelli, Eva Riccomagno
A geometric characterization of sensitivity analysis in monomial models. Int. J. Approx. Reason. 151 (2022)
Federico Carli, Manuele Leonelli, Eva Riccomagno, Gherardo Varando
Package stagedtrees for Structural Learning of Stratified Staged Trees. J. Stat. Softw. 102 (6) (2022)
Rafael Ballester-Ripoll, Manuele Leonelli
Computing Sobol indices in probabilistic graphical models. Reliab. Eng. Syst. Saf. 225 (2022)
Rafael Ballester-Ripoll, Manuele Leonelli
You Only Derive Once (YODO): Automatic Differentiation for Efficient Sensitivity Analysis in Bayesian Networks. CoRR (2022)
Manuele Leonelli, Gherardo Varando
Highly Efficient Structural Learning of Sparse Staged Trees. CoRR (2022)
Manuele Leonelli, Gherardo Varando
Highly Efficient Structural Learning of Sparse Staged Trees. PGM (2022)
Manuele Leonelli, Ramsiya Ramanathan, Rachel L. Wilkerson
Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package. CoRR (2021)
Manuele Leonelli, Gherardo Varando
Context-Specific Causal Discovery for Categorical Data Using Staged Trees. CoRR (2021)
Rafael Ballester-Ripoll, Manuele Leonelli
Global sensitivity analysis in probabilistic graphical models. CoRR (2021)
Gherardo Varando, Federico Carli, Manuele Leonelli
Staged trees and asymmetry-labeled DAGs. CoRR (2021)
Federico Carli, Manuele Leonelli, Gherardo Varando
A new class of generative classifiers based on staged tree models. CoRR (2020)
Christiane Görgen, Manuele Leonelli
Model-Preserving Sensitivity Analysis for Families of Gaussian Distributions. J. Mach. Learn. Res. 21 (2020)
Manuele Leonelli, Dani Gamerman
Semiparametric bivariate modelling with flexible extremal dependence. Stat. Comput. 30 (2) (2020)
Manuele Leonelli, Eva Riccomagno, Jim Q. Smith
Coherent combination of probabilistic outputs for group decision making: an algebraic approach. OR Spectr. 42 (2) (2020)
Manuele Leonelli, Eva Riccomagno
A geometric characterisation of sensitivity analysis in monomial models. CoRR (2019)
Manuele Leonelli
Sensitivity analysis beyond linearity. Int. J. Approx. Reason. 113 (2019)
Christiane Görgen, Manuele Leonelli
Model-Preserving Sensitivity Analysis for Families of Gaussian Distributions. CoRR (2018)
Manuele Leonelli, Jim Q. Smith
Directed Expected Utility Networks. Decis. Anal. 14 (2) (2017)
Manuele Leonelli, Eva Riccomagno, Jim Q. Smith
A symbolic algebra for the computation of expected utilities in multiplicative influence diagrams. Ann. Math. Artif. Intell. 81 (3-4) (2017)
Manuele Leonelli, Christiane Görgen, Jim Q. Smith
Sensitivity analysis in multilinear probabilistic models. Inf. Sci. 411 (2017)
Manuele Leonelli, Jim Q. Smith
Directed expected utility networks. CoRR (2016)
Manuele Leonelli, Eva Riccomagno, Jim Q. Smith
A symbolic algebra for the computation of expected utilities in multiplicative influence diagrams. CoRR (2016)
Christiane Görgen, Manuele Leonelli, James Q. Smith
A Differential Approach for Staged Trees. ECSQARU (2015)
Manuele Leonelli, James Q. Smith
Bayesian decision support for complex systems with many distributed experts. Ann. Oper. Res. 235 (1) (2015)
Manuele Leonelli, Christiane Görgen, Jim Q. Smith
Sensitivity analysis, multilinearity and beyond. CoRR (2015)
Manuele Leonelli, James Q. Smith
Using graphical models and multi-attribute utility theory for probabilistic uncertainty handling in large systems, with application to the nuclear emergency management. ICDE Workshops (2013)