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2020 – today
- 2024
[j5]Seyum Abebe, Irene Poli, Roger D. Jones
, Debora Slanzi:
Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning. Mach. Learn. Knowl. Extr. 6(3): 1798-1817 (2024)- 2023
- [j4]Debora Slanzi, Valentina Mameli, Philip J. Brown:
A comparative study on high-dimensional bayesian regression with binary predictors. Commun. Stat. Simul. Comput. 52(5): 1979-1999 (2023) - [c9]Debora Slanzi, Claudio Silvestri, Irene Poli, Gert Mayer:
Exploiting the Potential of Bayesian Networks in Deriving New Insight into Diabetic Kidney Disease (DKD). WIVACE 2023: 298-308 - 2020
- [c8]Tewodros Mulugeta Dagnew, Claudio Silvestri, Debora Slanzi, Irene Poli:
A Neural Network Model for Lead Optimization of MMP12 Inhibitors. ICPR Workshops (4) 2020: 323-335
2010 – 2019
- 2018
- [c7]Shira Fano, Debora Slanzi:
Evolution of Workers' Behaviour in Dual Labor Markets. WIVACE 2018: 45-56 - [e1]Marcello Pelillo, Irene Poli, Andrea Roli, Roberto Serra, Debora Slanzi, Marco Villani:
Artificial Life and Evolutionary Computation - 12th Italian Workshop, WIVACE 2017, Venice, Italy, September 19-21, 2017, Revised Selected Papers. Communications in Computer and Information Science 830, Springer 2018, ISBN 978-3-319-78657-5 [contents] - 2017
- [c6]Shira Fano, Debora Slanzi:
Using Twitter Data to Monitor Political Campaigns and Predict Election Results. PAAMS (Special Sessions) 2017: 191-197 - [c5]Debora Slanzi, Valentina Anzoise, Irene Poli:
Modeling Urbanization Perception: Emerging Topics on Hangzhou Future Sci-Tech City Development. WIVACE 2017: 229-239 - [c4]Debora Slanzi, Valentina Mameli, Marina Khoroshiltseva, Irene Poli:
Multi-objective Optimization in High-Dimensional Molecular Systems. WIVACE 2017: 284-295 - 2016
- [c3]Alessandro Giovannelli, Debora Slanzi, Marina Khoroshiltseva, Irene Poli:
Model-Based Lead Molecule Design. WIVACE 2016: 103-113 - [c2]Valentina Mameli, Nicola Lunardon, Marina Khoroshiltseva, Debora Slanzi, Irene Poli:
Reducing Dimensionality in Molecular Systems: A Bayesian Non-parametric Approach. WIVACE 2016: 114-125 - 2015
- [p1]Davide De March, Matteo Borrotti, Luca Sartore, Debora Slanzi, Lorenzo Podestà, Irene Poli:
A Predictive Approach Based on Neural Network Models for Building Automation Systems. Advances in Neural Networks 2015: 253-262 - 2014
- [j3]Matteo Borrotti, Davide De March, Debora Slanzi, Irene Poli:
Designing Lead Optimisation of MMP-12 Inhibitors. Comput. Math. Methods Medicine 2014: 258627:1-258627:8 (2014) - [c1]Debora Slanzi, Matteo Borrotti, Davide De March, Daniele Orlando, Silvio Giove, Irene Poli:
Qualitative Particle Swarm Optimization (Q-PSO) for Energy-Efficient Building Designs. WIVACE 2014: 13-25 - 2010
- [j2]Adriana Brogini, Debora Slanzi:
On using Bayesian networks for complexity reduction in decision trees. Stat. Methods Appl. 19(1): 127-139 (2010)
2000 – 2009
- 2009
- [j1]Giovanni Minervini, Giuseppe Evangelista, Laura Villanova, Debora Slanzi, Davide De Lucrezia, Irene Poli, Pier Luigi Luisi, Fabio Polticelli:
Massive non-natural proteins structure prediction using grid technologies. BMC Bioinform. 10(S-6) (2009)
Coauthor Index
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