Antonio Vergari
Title
Cited by
Cited by
Year
Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning
A Vergari, N Di Mauro, F Esposito
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
712015
Mixed sum-product networks: A deep architecture for hybrid domains
A Molina, A Vergari, N Di Mauro, S Natarajan, F Esposito, K Kersting
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
422018
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
R Peharz, A Vergari, K Stelzner, A Molina, X Shao, M Trapp, K Kersting, ...
Proceedings of UAI, 2019
25*2019
Visualizing and understanding sum-product networks
A Vergari, N Di Mauro, F Esposito
Machine Learning 108 (4), 551-573, 2019
192019
Learning Accurate Cutset Networks by Exploiting Decomposability
N Di Mauro, A Vergari, F Esposito
AI* IA 2015, Advances in Artificial Intelligence, 221-232, 2015
152015
From Variational to Deterministic Autoencoders
P Ghosh, MSM Sajjadi, A Vergari, M Black, B Schölkopf
arXiv preprint arXiv:1903.12436, 2019
142019
Sum-product autoencoding: Encoding and decoding representations using sum-product networks
A Vergari, R Peharz, N Di Mauro, A Molina, K Kersting, F Esposito
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
142018
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks
A Molina, A Vergari, K Stelzner, R Peharz, P Subramani, N Di Mauro, ...
arXiv preprint arXiv:1901.03704, 2019
13*2019
Learning Bayesian Random Cutset Forests
N Di Mauro, A Vergari, TMA Basile
International Symposium on Methodologies for Intelligent Systems, 122-132, 2015
112015
Automatic Bayesian density analysis
A Vergari, A Molina, R Peharz, Z Ghahramani, K Kersting, I Valera
Proceedings of the AAAI Conference on Artificial Intelligence 33, 5207-5215, 2019
92019
Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks
N Di Mauro, A Vergari, TMA Basile, F Esposito
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
92017
Multi-Label Classification with Cutset Networks
N Di Mauro, A Vergari, F Esposito
Proceedings of the Eighth International Conference on Probabilistic …, 2016
92016
End-to-end Learning of Deep Spatio-temporal Representations for Satellite Image Time Series Classification
N Di Mauro, A Vergari, TMA Basile, FG Ventola, F Esposito
Proceedings of the ECML/PKDD Discovery Challenges co-located with European …, 2017
82017
Density Estimators for Positive-Unlabeled Learning
TMA Basile, N Di Mauro, F Esposito, S Ferilli, A Vergari
International Workshop on New Frontiers in Mining Complex Patterns, 49-64, 2017
4*2017
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures
X Shao, A Molina, A Vergari, K Stelzner, R Peharz, T Liebig, K Kersting
arXiv preprint arXiv:1905.08550, 2019
32019
Alternative Variable Splitting Methods to Learn Sum-Product Networks
N Di Mauro, F Esposito, FG Ventola, A Vergari
Conference of the Italian Association for Artificial Intelligence, 334-346, 2017
32017
On Tractable Computation of Expected Predictions
P Khosravi, YJ Choi, Y Liang, A Vergari, G Van den Broeck
Advances in Neural Information Processing Systems, 11167-11178, 2019
22019
Sum-Product Network structure learning by efficient product nodes discovery
N Di Mauro, F Esposito, FG Ventola, A Vergari
Intelligenza Artificiale 12 (2), 143-159, 2018
22018
Ensembles of density estimators for positive-unlabeled learning
TMA Basile, N Di Mauro, F Esposito, S Ferilli, A Vergari
Journal of Intelligent Information Systems 53 (2), 199-217, 2019
12019
Bayesian Nonparametric Hawkes Processes
J Kapoor, A Vergari, MG Rodriguez, I Valera
All of Bayesian Nonparametrics: Especially the Useful Bits (BNP@ NeurIPS 2018), 2018
12018
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Articles 1–20