Antonio Vergari

114 papers A* 22A 6B 2C 3Journal 67Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Sobering Look at Tabular Data Generation via Probabilistic Circuits. CoRR Davide Scassola, Dylan Ponsford, Adrián Javaloy, Sebastiano Saccani, Luca Bortolussi, Henry Gouk, Antonio Vergari
2026	J	`jnl`	An Embarrassingly Simple Way to Optimize Orthogonal Matrices at Scale. CoRR Adrián Javaloy, Antonio Vergari
2026	J	`jnl`	Can LLMs Compress (and Decompress)? Evaluating Code Understanding and Execution via Invertibility. CoRR Nickil Maveli, Antonio Vergari, Shay B. Cohen
2026	J	`jnl`	Can VLMs Reason Robustly? A Neuro-Symbolic Investigation. CoRR Weixin Chen, Antonio Vergari, Han Zhao
2026	J	`jnl`	The Theory and Practice of MAP Inference over Non-Convex Constraints. CoRR Leander Kurscheidt, Gabriele Masina, Roberto Sebastiani, Antonio Vergari
2026	J	`jnl`	To Neuro-Symbolic Classification and Beyond by Compiling Description Logic Ontologies to Probabilistic Circuits. CoRR Nicolas Lazzari, Valentina Presutti, Antonio Vergari
2025	A	`conf`	A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction. UAI Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani, Andrea Passerini, Antonio Vergari
2025	J	`jnl`	A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction. CoRR Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani, Andrea Passerini, Antonio Vergari
2025	J	`jnl`	COPA: Comparing the Incomparable to Explore the Pareto Front. CoRR Adrián Javaloy, Antonio Vergari, Isabel Valera
2025	J	`jnl`	Can LLMs subtract numbers? CoRR Mayank Jobanputra, Nils Philipp Walter, Maitrey Mehta, Blerta Veseli, Evan Parker Kelly Chapple, Yifan Wang, Sneha Chetani, Ellie Pavlick, Antonio Vergari, Vera Demberg
2025	—	`conf`	Can interpretability and accuracy coexist in cancer survival analysis? MLHC Piyush Borole, Tongjie Wang, Antonio Vergari, Ajitha Rajan
2025	J	`jnl`	Fast and Expressive Multi-Token Prediction with Probabilistic Circuits. CoRR Andreas Grivas, Lorenzo Loconte, Emile van Krieken, Piotr Nawrot, Yu Zhao, Euan Wielewski, Pasquale Minervini, Edoardo Maria Ponti, Antonio Vergari
2025	J	`jnl`	How to Square Tensor Networks and Circuits Without Squaring Them. CoRR Lorenzo Loconte, Adrián Javaloy, Antonio Vergari
2025	A*	`conf`	Is Complex Query Answering Really Complex? ICML Cosimo Gregucci, Bo Xiong, Daniel Hernández, Lorenzo Loconte, Pasquale Minervini, Steffen Staab, Antonio Vergari
2025	A*	`conf`	Logically Consistent Language Models via Neuro-Symbolic Integration. ICLR Diego Calanzone, Stefano Teso, Antonio Vergari
2025	J	`jnl`	Neurosymbolic Diffusion Models. CoRR Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari
2025	C	`conf`	Neurosymbolic Reasoning Shortcuts under the Independence Assumption. NeSy Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari
2025	J	`jnl`	Neurosymbolic Reasoning Shortcuts under the Independence Assumption. CoRR Emile van Krieken, Pasquale Minervini, Edoardo Maria Ponti, Antonio Vergari
2025	A*	`conf`	SEMMA: A Semantic Aware Knowledge Graph Foundation Model. EMNLP Arvindh Arun, Sumit Kumar, Mojtaba Nayyeri, Bo Xiong, Ponnurangam Kumaraguru, Antonio Vergari, Steffen Staab
2025	J	`jnl`	SEMMA: A Semantic Aware Knowledge Graph Foundation Model. CoRR Arvindh Arun, Sumit Kumar, Mojtaba Nayyeri, Bo Xiong, Ponnurangam Kumaraguru, Antonio Vergari, Steffen Staab
2025	J	`jnl`	Scalable Expectation Estimation with Subtractive Mixture Models. CoRR Lena Zellinger, Nicola Branchini, Víctor Elvira, Antonio Vergari
2025	A*	`conf`	Sum of Squares Circuits. AAAI Lorenzo Loconte, Stefan Mengel, Antonio Vergari
2025	J	`jnl`	Symbol Grounding in Neuro-Symbolic AI: A Gentle Introduction to Reasoning Shortcuts. CoRR Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Paolo Morettin, Elena Umili, Antonio Vergari, Efthymia Tsamoura, Andrea Passerini, Stefano Teso
2025	J	`jnl`	Tractable Representation Learning with Probabilistic Circuits. CoRR Steven Braun, Sahil Sidheekh, Antonio Vergari, Martin Mundt, Sriraam Natarajan, Kristian Kersting
2025	J	`jnl`	Tractable Representation Learning with Probabilistic Circuits. Trans. Mach. Learn. Res. Steven Braun, Sahil Sidheekh, Antonio Vergari, Martin Mundt, Sriraam Natarajan, Kristian Kersting
2025	—	`conf`	What can Large Language Models Capture about Code Functional Equivalence? NAACL (Findings) Nickil Maveli, Antonio Vergari, Shay B. Cohen
2025	J	`jnl`	What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)? Trans. Mach. Learn. Res. Lorenzo Loconte, Antonio Mari, Gennaro Gala, Robert Peharz, Cassio de Campos, Erik Quaeghebeur, Gennaro Vessio, Antonio Vergari
2024	J	`jnl`	A Benchmark Suite for Systematically Evaluating Reasoning Shortcuts. CoRR Samuele Bortolotti, Emanuele Marconato, Tommaso Carraro, Paolo Morettin, Emile van Krieken, Antonio Vergari, Stefano Teso, Andrea Passerini
2024	A*	`conf`	A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts. NeurIPS Samuele Bortolotti, Emanuele Marconato, Tommaso Carraro, Paolo Morettin, Emile van Krieken, Antonio Vergari, Stefano Teso, Andrea Passerini
2024	A	`conf`	BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts. UAI Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso
2024	J	`jnl`	BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts. CoRR Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso
2024	B	`conf`	ChemAlgebra: Algebraic Reasoning on Chemical Reactions. IJCNN Andrea Valenti, Davide Bacciu, Antonio Vergari
2024	J	`jnl`	From MNIST to ImageNet and back: benchmarking continual curriculum learning. Mach. Learn. Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo
2024	J	`jnl`	Is Complex Query Answering Really Complex? CoRR Cosimo Gregucci, Bo Xiong, Daniel Hernández, Lorenzo Loconte, Pasquale Minervini, Steffen Staab, Antonio Vergari
2024	J	`jnl`	Logically Consistent Language Models via Neuro-Symbolic Integration. CoRR Diego Calanzone, Stefano Teso, Antonio Vergari
2024	J	`jnl`	On Faster Marginalization with Squared Circuits via Orthonormalization. CoRR Lorenzo Loconte, Antonio Vergari
2024	A*	`conf`	On the Independence Assumption in Neurosymbolic Learning. ICML Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari
2024	J	`jnl`	On the Independence Assumption in Neurosymbolic Learning. CoRR Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari
2024	—	`conf`	PIXAR: Auto-Regressive Language Modeling in Pixel Space. ACL (Findings) Yintao Tai, Xiyang Liao, Alessandro Suglia, Antonio Vergari
2024	J	`jnl`	PIXAR: Auto-Regressive Language Modeling in Pixel Space. CoRR Yintao Tai, Xiyang Liao, Alessandro Suglia, Antonio Vergari
2024	A	`conf`	Probabilistic Integral Circuits. AISTATS Gennaro Gala, Cassio P. de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur
2024	A*	`conf`	Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits. NeurIPS Gennaro Gala, Cassio P. de Campos, Antonio Vergari, Erik Quaeghebeur
2024	J	`jnl`	Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits. CoRR Gennaro Gala, Cassio de Campos, Antonio Vergari, Erik Quaeghebeur
2024	A*	`conf`	Subtractive Mixture Models via Squaring: Representation and Learning. ICLR Lorenzo Loconte, Aleksanteri M. Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari
2024	J	`jnl`	Sum of Squares Circuits. CoRR Lorenzo Loconte, Stefan Mengel, Antonio Vergari
2024	A*	`conf`	Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification. AAAI Andreas Grivas, Antonio Vergari, Adam Lopez
2024	J	`jnl`	Towards Logically Consistent Language Models via Probabilistic Reasoning. CoRR Diego Calanzone, Stefano Teso, Antonio Vergari
2024	J	`jnl`	What can Large Language Models Capture about Code Functional Equivalence? CoRR Nickil Maveli, Antonio Vergari, Shay B. Cohen
2024	J	`jnl`	What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)? CoRR Lorenzo Loconte, Antonio Mari, Gennaro Gala, Robert Peharz, Cassio de Campos, Erik Quaeghebeur, Gennaro Vessio, Antonio Vergari
2023	J	`jnl`	From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning. CoRR Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo
2023	J	`jnl`	How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits. CoRR Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
2023	A*	`conf`	How to Turn Your Knowledge Graph Embeddings into Generative Models. NeurIPS Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
2023	J	`jnl`	Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy Tasks. CoRR Aryo Pradipta Gema, Dominik Grabarczyk, Wolf De Wulf, Piyush Borole, Javier Antonio Alfaro, Pasquale Minervini, Antonio Vergari, Ajitha Rajan
2023	A*	`conf`	Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts. NeurIPS Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini
2023	J	`jnl`	Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts. CoRR Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini
2023	J	`jnl`	Probabilistic Integral Circuits. CoRR Gennaro Gala, Cassio P. de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur
2023	C	`conf`	Semantic Probabilistic Layers for Neuro-Symbolic Learning. NeSy Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
2023	J	`jnl`	Subtractive Mixture Models via Squaring: Representation and Learning. CoRR Lorenzo Loconte, Aleksanteri M. Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari
2023	J	`jnl`	Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification. CoRR Andreas Grivas, Antonio Vergari, Adam Lopez
2023	J	`jnl`	Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning. CoRR Filippo Corponi, Bryan M. Li, Gerard Anmella, Clàudia Valenzuela-Pascual, Ariadna Mas, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antonio Benabarre, Marina Garriga, Eduard Vieta, Allan H. Young, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, Antonio Vergari
2022	J	`jnl`	ChemAlgebra: Algebraic Reasoning on Chemical Reactions. CoRR Andrea Valenti, Davide Bacciu, Antonio Vergari
2022	J	`jnl`	Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
2022	J	`jnl`	Efficient and Reliable Probabilistic Interactive Learning with Structured Outputs. CoRR Stefano Teso, Antonio Vergari
2022	J	`jnl`	Recent Advancements in Tractable Probabilistic Inference (Dagstuhl Seminar 22161). Dagstuhl Reports Priyank Jaini, Kristian Kersting, Antonio Vergari, Max Welling
2022	A*	`conf`	Semantic Probabilistic Layers for Neuro-Symbolic Learning. NeurIPS Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
2022	J	`jnl`	Semantic Probabilistic Layers for Neuro-Symbolic Learning. CoRR Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
2022	J	`jnl`	Strudel: A fast and accurate learner of structured-decomposable probabilistic circuits. Int. J. Approx. Reason. Meihua Dang, Antonio Vergari, Guy Van den Broeck
2021	A*	`conf`	A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference. NeurIPS Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck
2021	J	`jnl`	A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries. CoRR Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck
2021	A	`conf`	An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games. EACL Alessandro Suglia, Yonatan Bisk, Ioannis Konstas, Antonio Vergari, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon
2021	J	`jnl`	An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games. CoRR Alessandro Suglia, Yonatan Bisk, Ioannis Konstas, Antonio Vergari, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon
2021	A*	`conf`	Juice: A Julia Package for Logic and Probabilistic Circuits. AAAI Meihua Dang, Pasha Khosravi, Yitao Liang, Antonio Vergari, Guy Van den Broeck
2021	—	`conf`	Neural Concept Formation in Knowledge Graphs. AKBC Agnieszka Dobrowolska, Antonio Vergari, Pasquale Minervini
2021	J	`jnl`	Tractable Computation of Expected Kernels by Circuits. CoRR Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck
2021	A	`conf`	Tractable computation of expected kernels. UAI Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck
2020	—	`conf`	Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
2020	A*	`conf`	Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
2020	J	`jnl`	Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. CoRR Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
2020	A*	`conf`	From Variational to Deterministic Autoencoders. ICLR Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schölkopf
2020	J	`jnl`	Handling Missing Data in Decision Trees: A Probabilistic Approach. CoRR Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck
2020	B	`conf`	Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games. COLING Alessandro Suglia, Antonio Vergari, Ioannis Konstas, Yonatan Bisk, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon
2020	J	`jnl`	Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games. CoRR Alessandro Suglia, Antonio Vergari, Ioannis Konstas, Yonatan Bisk, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon
2020	A*	`conf`	Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations. NeurIPS Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck
2020	A*	`conf`	Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing. ICML Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck
2020	J	`jnl`	Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing. CoRR Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck
2020	—	`conf`	Strudel: Learning Structured-Decomposable Probabilistic Circuits. PGM Meihua Dang, Antonio Vergari, Guy Van den Broeck
2020	J	`jnl`	Strudel: Learning Structured-Decomposable Probabilistic Circuits. CoRR Meihua Dang, Antonio Vergari, Guy Van den Broeck
2019	A*	`conf`	Automatic Bayesian Density Analysis. AAAI Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera
2019	J	`jnl`	Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
2019	J	`jnl`	Ensembles of density estimators for positive-unlabeled learning. J. Intell. Inf. Syst. Teresa Maria Altomare Basile, Nicola Di Mauro, Floriana Esposito, Stefano Ferilli, Antonio Vergari
2019	J	`jnl`	From Variational to Deterministic Autoencoders. CoRR Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schölkopf
2019	J	`jnl`	Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing. CoRR Zhe Zeng, Fanqi Yan, Paolo Morettin, Antonio Vergari, Guy Van den Broeck
2019	A*	`conf`	On Tractable Computation of Expected Predictions. NeurIPS Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck
2019	J	`jnl`	On Tractable Computation of Expected Predictions. CoRR Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck
2019	A	`conf`	Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani
2019	J	`jnl`	SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting
2019	J	`jnl`	Visualizing and understanding Sum-Product Networks. Mach. Learn. Antonio Vergari, Nicola Di Mauro, Floriana Esposito
2018	J	`jnl`	Automatic Bayesian Density Analysis. CoRR Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera
2018	A*	`conf`	Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains. AAAI Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting
2018	J	`jnl`	Probabilistic Deep Learning using Random Sum-Product Networks. CoRR Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani
2018	A*	`conf`	Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks. AAAI Antonio Vergari, Robert Peharz, Nicola Di Mauro, Alejandro Molina, Kristian Kersting, Floriana Esposito
2018	J	`jnl`	Sum-Product Network structure learning by efficient product nodes discovery. Intelligenza Artificiale Nicola Di Mauro, Floriana Esposito, Fabrizio Giuseppe Ventola, Antonio Vergari
2017	—	`conf`	Alternative Variable Splitting Methods to Learn Sum-Product Networks. AI*IA Nicola Di Mauro, Floriana Esposito, Fabrizio Giuseppe Ventola, Antonio Vergari
2017	—	`conf`	Density Estimators for Positive-Unlabeled Learning. NFMCP@PKDD/ECML Teresa Maria Altomare Basile, Nicola Di Mauro, Floriana Esposito, Stefano Ferilli, Antonio Vergari
2017	—	`conf`	Encoding and Decoding Representations with Sum- and Max-Product Networks. ICLR (Workshop) Antonio Vergari, Robert Peharz, Nicola Di Mauro, Floriana Esposito
2017	—	`conf`	End-to-end Learning of Deep Spatio-temporal Representations for Satellite Image Time Series Classification. DC@PKDD/ECML Nicola Di Mauro, Antonio Vergari, Teresa Maria Altomare Basile, Fabrizio Giuseppe Ventola, Floriana Esposito
2017	—	`conf`	Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks. ECML/PKDD (1) Nicola Di Mauro, Antonio Vergari, Teresa Maria Altomare Basile, Floriana Esposito
2017	J	`jnl`	Sum-Product Networks for Hybrid Domains. CoRR Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting
2016	—	`conf`	Multi-Label Classification with Cutset Networks. Probabilistic Graphical Models Nicola Di Mauro, Antonio Vergari, Floriana Esposito
2016	J	`jnl`	Towards Representation Learning with Tractable Probabilistic Models. CoRR Antonio Vergari, Nicola Di Mauro, Floriana Esposito
2016	J	`jnl`	Visualizing and Understanding Sum-Product Networks. CoRR Antonio Vergari, Nicola Di Mauro, Floriana Esposito
2015	—	`conf`	Learning Accurate Cutset Networks by Exploiting Decomposability. AI*IA Nicola Di Mauro, Antonio Vergari, Floriana Esposito
2015	C	`conf`	Learning Bayesian Random Cutset Forests. ISMIS Nicola Di Mauro, Antonio Vergari, Teresa Maria Altomare Basile
2015	—	`conf`	Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning. ECML/PKDD (2) Antonio Vergari, Nicola Di Mauro, Floriana Esposito