My research here focuses on learning deep probabilistic models, exploiting them for exact and tractable inference, and ultimately aiming to automate machine learning, starting from density estimation for heterogeneous data. I am also interested in integrating symbolic and relational representations into statistical models.
ei
Kapoor, J., Vergari, A., Gomez Rodriguez, M., Valera, I.
Bayesian Nonparametric Hawkes Processes
Bayesian Nonparametrics workshop at the 32nd Conference on Neural Information Processing Systems, December 2018 (conference)
ei
Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I.
Automatic Bayesian Density Analysis
2018 (conference) Submitted
ei
Peharz, R., Vergari, A., Stelzner, K., Molina, A., Trapp, M., Kersting, K., Ghahramani, Z.
Probabilistic Deep Learning using Random Sum-Product Networks
2018 (conference) Submitted
ei
Vergari, A., Di Mauro, N., Esposito, F.
Visualizing and understanding Sum-Product Networks
Machine Learning, 2018 (article)
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