Alternative Variable Splitting Methods to Learn Sum-Product Networks. - Nicola Di Mauro; Floriana Esposito; Fabrizio Giuseppe Ventola; Antonio Vergari (AI*IA, 2017)

End-to-end Learning of Deep Spatio-temporal Representations for Satellite Image Time Series Classification. - Nicola Di Mauro; Antonio Vergari; Teresa Maria Altomare Basile; Fabrizio Giuseppe Ventola; Floriana Esposito (DC@PKDD/ECML, 2017)

Sum-Product Network structure learning by efficient product nodes discovery. - Nicola Di Mauro; Floriana Esposito; Fabrizio Giuseppe Ventola; Antonio Vergari (Intelligenza Artificiale, 2018)

Random Sum-Product Forests with Residual Links. - Fabrizio Ventola; Karl Stelzner; Alejandro Molina 001; Kristian Kersting (CoRR, 2019)

Residual Sum-Product Networks. - Fabrizio Ventola; Karl Stelzner; Alejandro Molina 001; Kristian Kersting (PGM, 2020)

Whittle Networks: A Deep Likelihood Model for Time Series. - Zhongjie Yu 001; Fabrizio Ventola; Kristian Kersting (ICML, 2021)

Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. - Fabrizio Ventola; Devendra Singh Dhami; Kristian Kersting (ILP, 2021)

Elevating Perceptual Sample Quality in PCs through Differentiable Sampling. - Steven Lang; Martin Mundt; Fabrizio Ventola; Robert Peharz; Kristian Kersting (Pre-Registration Workshop @ NeurIPS, 2021)

User Label Leakage from Gradients in Federated Learning. - Aidmar Wainakh; Fabrizio Ventola; Till Müßig; Jens Keim; Carlos Garcia Cordero; Ephraim Zimmer; Tim Grube; Kristian Kersting; Max Mühlhäuser (CoRR, 2021)

RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting. - Nils Thoma; Zhongjie Yu 001; Fabrizio Ventola; Kristian Kersting (CoRR, 2021)

DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection. - Steven Lang; Fabrizio Ventola; Kristian Kersting (CoRR, 2021)

Predictive Whittle networks for time series. - Zhongjie Yu 001; Fabrizio Ventola; Nils Thoma; Devendra Singh Dhami; Martin Mundt; Kristian Kersting (UAI, 2022)

User-Level Label Leakage from Gradients in Federated Learning. - Aidmar Wainakh; Fabrizio Ventola; Till Müßig; Jens Keim; Carlos Garcia Cordero; Ephraim Zimmer; Tim Grube; Kristian Kersting; Max Mühlhäuser (Proc. Priv. Enhancing Technol., 2022)

Probabilistic circuits that know what they don't know. - Fabrizio Ventola; Steven Braun; Zhongjie Yu 001; Martin Mundt; Kristian Kersting (UAI, 2023)

Bi-Level One-Shot Architecture Search for Probabilistic Time Series Forecasting. - Jonas Seng; Fabian Kalter; Zhongjie Yu 001; Fabrizio Ventola; Kristian Kersting (AutoML, 2024)

Hyperparameter Optimization via Interacting with Probabilistic Circuits. - Jonas Seng; Fabrizio Ventola; Zhongjie Yu 001; Kristian Kersting (CoRR, 2025)