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.
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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)
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Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I.
Automatic Bayesian Density Analysis
2018 (conference) Submitted
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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
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Vergari, A., Di Mauro, N., Esposito, F.
Visualizing and understanding Sum-Product Networks
Machine Learning, 2018 (article)