Debora Slanzi - researchr alias

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Viewing Publication 1 - 14 from 14

2023

A comparative study on high-dimensional bayesian regression with binary predictorsDebora Slanzi, Valentina Mameli, Philip J. Brown. cssc, 52(5):1979-1999, May 2023. [doi]

Exploiting the Potential of Bayesian Networks in Deriving New Insight into Diabetic Kidney Disease (DKD)Debora Slanzi, Claudio Silvestri, Irene Poli, Gert Mayer. wivace 2024: 298-308 [doi]

2020

A Neural Network Model for Lead Optimization of MMP12 InhibitorsTewodros Mulugeta Dagnew, Claudio Silvestri, Debora Slanzi, Irene Poli. icpr 2021: 323-335 [doi]

2018

Evolution of Workers' Behaviour in Dual Labor MarketsShira Fano, Debora Slanzi. wivace 2019: 45-56 [doi]

2017

Using Twitter Data to Monitor Political Campaigns and Predict Election ResultsShira Fano, Debora Slanzi. paams 2018: 191-197 [doi]

Multi-objective Optimization in High-Dimensional Molecular SystemsDebora Slanzi, Valentina Mameli, Marina Khoroshiltseva, Irene Poli. wivace 2018: 284-295 [doi]

Modeling Urbanization Perception: Emerging Topics on Hangzhou Future Sci-Tech City DevelopmentDebora Slanzi, Valentina Anzoise, Irene Poli. wivace 2018: 229-239 [doi]

2016

Model-Based Lead Molecule DesignAlessandro Giovannelli, Debora Slanzi, Marina Khoroshiltseva, Irene Poli. wivace 2017: 103-113 [doi]

Reducing Dimensionality in Molecular Systems: A Bayesian Non-parametric ApproachValentina Mameli, Nicola Lunardon, Marina Khoroshiltseva, Debora Slanzi, Irene Poli. wivace 2017: 114-125 [doi]

2015

A Predictive Approach Based on Neural Network Models for Building Automation SystemsDavide De March, Matteo Borrotti, Luca Sartore, Debora Slanzi, Lorenzo Podestà, Irene Poli. In Simone Bassis, Anna Esposito, Francesco Carlo Morabito, editors, Advances in Neural Networks: Computational and Theoretical Issues. Volume 37 of Smart Innovation, Systems and Technologies, pages 253-262, Springer, 2015. [doi]

2014

Designing Lead Optimisation of MMP-12 InhibitorsMatteo Borrotti, Davide De March, Debora Slanzi, Irene Poli. cmmm, 2014, 2014. [doi]

Qualitative Particle Swarm Optimization (Q-PSO) for Energy-Efficient Building DesignsDebora Slanzi, Matteo Borrotti, Davide De March, Daniele Orlando, Silvio Giove, Irene Poli. wivace 2014: 13-25 [doi]

2010

On using Bayesian networks for complexity reduction in decision treesAdriana Brogini, Debora Slanzi. sma, 19(1):127-139, 2010. [doi]

2009

Massive non-natural proteins structure prediction using grid technologiesGiovanni Minervini, Giuseppe Evangelista, Laura Villanova, Debora Slanzi, Davide De Lucrezia, Irene Poli, Pier Luigi Luisi, Fabio Polticelli. bmcbi, 10(S-6), 2009. [doi]

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