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ORCIDFabrizio Ventola
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- affiliation: TU Darmstadt, Department of Computer Science, Darmstadt, Germany
- affiliation: University of Bari, Department of Computer Science, Bari, Italy
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Journal Articles
- 2022
[j2]Aidmar Wainakh, Fabrizio Ventola, Till Müßig, Jens Keim, Carlos Garcia Cordero, Ephraim Zimmer
, Tim Grube, Kristian Kersting, Max Mühlhäuser:
User-Level Label Leakage from Gradients in Federated Learning. Proc. Priv. Enhancing Technol. 2022(2): 227-244 (2022)- 2018
- [j1]Nicola Di Mauro, Floriana Esposito, Fabrizio Giuseppe Ventola, Antonio Vergari:
Sum-Product Network structure learning by efficient product nodes discovery. Intelligenza Artificiale 12(2): 143-159 (2018)
Conference and Workshop Papers
- 2024
- [c9]Jonas Seng, Fabian Kalter, Zhongjie Yu, Fabrizio Ventola, Kristian Kersting:
Bi-Level One-Shot Architecture Search for Probabilistic Time Series Forecasting. AutoML 2024: 10/1-20 - 2023
- [c8]Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting:
Probabilistic circuits that know what they don't know. UAI 2023: 2157-2167 - 2022
- [c7]Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting:
Predictive Whittle networks for time series. UAI 2022: 2320-2330 - 2021
- [c6]Zhongjie Yu, Fabrizio Ventola, Kristian Kersting:
Whittle Networks: A Deep Likelihood Model for Time Series. ICML 2021: 12177-12186 - [c5]Fabrizio Ventola, Devendra Singh Dhami, Kristian Kersting:
Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. ILP 2021: 251-265 - [c4]Steven Lang, Martin Mundt, Fabrizio Ventola, Robert Peharz, Kristian Kersting:
Elevating Perceptual Sample Quality in PCs through Differentiable Sampling. Pre-Registration Workshop @ NeurIPS 2021: 1-25 - 2020
- [c3]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Residual Sum-Product Networks. PGM 2020: 545-556 - 2017
- [c2]Nicola Di Mauro, Floriana Esposito, Fabrizio Giuseppe Ventola, Antonio Vergari:
Alternative Variable Splitting Methods to Learn Sum-Product Networks. AI*IA 2017: 334-346 - [c1]Nicola Di Mauro, Antonio Vergari, Teresa Maria Altomare Basile, Fabrizio Giuseppe Ventola, Floriana Esposito:
End-to-end Learning of Deep Spatio-temporal Representations for Satellite Image Time Series Classification. DC@PKDD/ECML 2017
Informal and Other Publications
- 2023
- [i5]Fabrizio Ventola, Steven Braun, Zhongjie Yu, Martin Mundt, Kristian Kersting:
Probabilistic Circuits That Know What They Don't Know. CoRR abs/2302.06544 (2023) - 2021
- [i4]Aidmar Wainakh, Fabrizio Ventola, Till Müßig, Jens Keim, Carlos Garcia Cordero, Ephraim Zimmer, Tim Grube, Kristian Kersting, Max Mühlhäuser:
User Label Leakage from Gradients in Federated Learning. CoRR abs/2105.09369 (2021) - [i3]Nils Thoma, Zhongjie Yu, Fabrizio Ventola, Kristian Kersting:
RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting. CoRR abs/2106.04148 (2021) - [i2]Steven Lang, Fabrizio Ventola, Kristian Kersting:
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection. CoRR abs/2109.06148 (2021) - 2019
- [i1]Fabrizio Ventola, Karl Stelzner, Alejandro Molina, Kristian Kersting:
Random Sum-Product Forests with Residual Links. CoRR abs/1908.03250 (2019)
Coauthor Index
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