Asperti, Andrea; Del Brutto, Marco, MicroRacer: A Didactic Environment for Deep Reinforcement Learning, in: International Conference on Machine Learning, Optimization, and Data Science, «LECTURE NOTES IN COMPUTER SCIENCE», 2023, 13810, pp. 239 - 252 (atti di: International Conference on Machine Learning, Optimization, and Data Science - LOD 2022, Certosa di Pontignano, Siena, Italy, 18-22 settembre 2022) [Contributo in Atti di convegno]
Asperti, Andrea; Tonelli, Valerio, Comparing the latent space of generative models, «NEURAL COMPUTING & APPLICATIONS», 2022, Early Access, pp. 1 - 18 [articolo]
Asperti A.; Bugo L.; Filippini D., Enhancing variational generation through self-decomposition, «IEEE ACCESS», 2022, 10, pp. 67510 - 67520 [articolo]Open Access
Asperti, Andrea; Evangelista, Davide; Loli Piccolomini, Elena, A Survey on Variational Autoencoders from a Green AI Perspective, «SN COMPUTER SCIENCE», 2021, 2, Article number: 301, pp. 1 - 23 [articolo]Open Access
Asperti, Andrea; Evangelista, Davide; Marzolla, Moreno, Dissecting FLOPs Along Input Dimensions for GreenAI Cost Estimations, in: International Conference on Machine Learning, Optimization, and Data Science, Springer, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2021, 13164, pp. 86 - 100 (atti di: The 7th International Conference on Machine Learning Optimization Data Science, LOD 2021, Grasmere, United Kingdom, 4-8 october 2021) [Contributo in Atti di convegno]Open Access
Asperti, Andrea; Dal Bianco, Stefano, Syllabification of the Divine Comedy, «ACM JOURNAL ON COMPUTING AND CULTURAL HERITAGE», 2021, 14, pp. 1 - 26 [articolo]
Asperti, Andrea; Trentin, Matteo, Balancing Reconstruction Error and Kullback-Leibler Divergence in Variational Autoencoders, «IEEE ACCESS», 2020, 8, pp. 199440 - 199448 [articolo]Open Access
Asperti, Andrea; Cortesi, Daniele; De Pieri, Carlo; Pedrini, Gianmaria; Sovrano, Francesco, Crawling in Rogue's Dungeons With Deep Reinforcement Techniques, «IEEE TRANSACTIONS ON GAMES», 2020, 12, pp. 177 - 186 [articolo]
Asperti, Andrea, Variance Loss in Variational Autoencoders, in: Machine Learning, Optimization, and Data Science. LOD 2020., Springer, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2020, 12565, pp. 297 - 308 (atti di: Machine Learning, Optimization, and Data Science. LOD 2020., Certosa di Pontignano, Siena, Italy, July 19-23, 2020) [Contributo in Atti di convegno]Open Access
Asperti, Andrea, About Generative Aspects of Variational Autoencoders, in: Machine Learning, Optimization, and Data Science - 5th International Conference, LOD 2019, Siena, Italy, September 10-13, 2019, Proceedings, «LECTURE NOTES IN ARTIFICIAL INTELLIGENCE», 2019, 11943, pp. 71 - 82 (atti di: Machine Learning, Optimization, and Data Science - 5th International Conference, LOD 2019, Siena, Italy, September 10-13, September 10-13, 2019) [Contributo in Atti di convegno]
Asperti, Andrea; Cortesi, Daniele; Sovrano, Francesco, Crawling in Rogue’s Dungeons with (Partitioned) A3C, in: Machine Learning, Optimization, and Data Science - 4th International Conference, {LOD} 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers, Springer, 2019, 11331, pp. 264 - 275 (atti di: Machine Learning, Optimization, and Data Science - 4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018) [Contributo in Atti di convegno]
A. Asperti, Sparsity in Variational Autoencoders, in: A.Asperti, Proceedings of the first International Conference on Advances in Signal Processing and Artificial Intelligence, Barcelona, IFSA Publishing, 2019, pp. 18 - 22 (atti di: First International Conference on Advances in Signal Processing and Artificial Intelligence, Barcelona, 20-22 marzo 2019) [Contributo in Atti di convegno]
Andrea Asperti, Variational Autoencoders and the Variable Collapse Phenomenon, «SENSORS & TRANSDUCERS», 2019, 234, pp. 1 - 8 [articolo]Open Access
Andrea Asperti; Pietro Battilana, Automatic point-of-interest image cropping via ensembled convolutionalization, «INTERNATIONAL JOURNAL OF NEURAL NETWORKS AND ADVANCED APPLICATIONS», 2018, 5, pp. 17 - 24 [articolo]
Mastronardo, Claudio; Asperti, Andrea, The Effectiveness of Data Augmentation for Detection of Gastrointestinal Diseases from Endoscopical Images, in: Mastronardo, Claudio, Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies, 2018, pp. 199 - 205 (atti di: 11th International Joint Conference on Biomedical Engineering Systems and Technologies, Funchal, Madeira, Portugal, January 19-21 2018) [Contributo in Atti di convegno]
