Vergari, Antonio

43 publications

UAI 2025 A Probabilistic Neuro-Symbolic Layer for Algebraic Constraint Satisfaction Leander Kurscheidt, Paolo Morettin, Roberto Sebastiani, Andrea Passerini, Antonio Vergari

MLHC 2025 Can Interpretability and Accuracy Coexist in Cancer Survival Analysis? Piyush Borole, Tongjie Wang, Antonio Vergari, Ajitha Rajan

ICML 2025 Is Complex Query Answering Really Complex? Cosimo Gregucci, Bo Xiong, Daniel Hernández, Lorenzo Loconte, Pasquale Minervini, Steffen Staab, Antonio Vergari

ICLR 2025 Logically Consistent Language Models via Neuro-Symbolic Integration Diego Calanzone, Stefano Teso, Antonio Vergari

NeurIPS 2025 Neurosymbolic Diffusion Models Emile van Krieken, Pasquale Minervini, Edoardo Ponti, Antonio Vergari

AAAI 2025 Sum of Squares Circuits Lorenzo Loconte, Stefan Mengel, Antonio Vergari

TMLR 2025 Tractable Representation Learning with Probabilistic Circuits Steven Braun, Sahil Sidheekh, Antonio Vergari, Martin Mundt, Sriraam Natarajan, Kristian Kersting

TMLR 2025 What Is the Relationship Between Tensor Factorizations and Circuits (and How Can We Exploit It)? Lorenzo Loconte, Antonio Mari, Gennaro Gala, Robert Peharz, Cassio de Campos, Erik Quaeghebeur, Gennaro Vessio, Antonio Vergari

NeurIPS 2024 A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts Samuele Bortolotti, Emanuele Marconato, Tommaso Carraro, Paolo Morettin, Emile van Krieken, Antonio Vergari, Stefano Teso, Andrea Passerini

UAI 2024 BEARS Make Neuro-Symbolic Models Aware of Their Reasoning Shortcuts Emanuele Marconato, Samuele Bortolotti, Emile Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso

MLJ 2024 From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo

ICLRW 2024 Galerkin Meets Laplace: Fast Uncertainty Estimation in Neural PDEs Christian Jimenez Beltran, Antonio Vergari, Aretha L Teckentrup, Konstantinos C. Zygalakis

NeurIPSW 2024 Logically Consistent Language Models via Neuro-Symbolic Integration Diego Calanzone, Stefano Teso, Antonio Vergari

ICML 2024 On the Independence Assumption in Neurosymbolic Learning Emile Van Krieken, Pasquale Minervini, Edoardo Ponti, Antonio Vergari

AISTATS 2024 Probabilistic Integral Circuits Gennaro Gala, Cassio Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur

NeurIPS 2024 Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits Gennaro Gala, Cassio de Campos, Antonio Vergari, Erik Quaeghebeur

ICLR 2024 Subtractive Mixture Models via Squaring: Representation and Learning Lorenzo Loconte, Aleksanteri Mikulus Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari

AAAI 2024 Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification Andreas Grivas, Antonio Vergari, Adam Lopez

ICLRW 2024 Towards Logically Consistent Language Models via Probabilistic Reasoning Diego Calanzone, Antonio Vergari, Stefano Teso

NeurIPS 2023 How to Turn Your Knowledge Graph Embeddings into Generative Models Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari

NeurIPS 2023 Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini

NeurIPSW 2022 Inferring Mood Disorder Symptoms from Multivariate Time-Series Sensory Data Bryan M. Li, Filippo Corponi, Gerard Anmella, Ariadna Mas, Miriam Sanabra, Diego Hidalgo-Mazzei, Antonio Vergari

NeurIPS 2022 Semantic Probabilistic Layers for Neuro-Symbolic Learning Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari

NeurIPS 2021 A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck

AAAI 2021 Juice: A Julia Package for Logic and Probabilistic Circuits Meihua Dang, Pasha Khosravi, Yitao Liang, Antonio Vergari, Guy Van den Broeck

UAI 2021 Tractable Computation of Expected Kernels Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Broeck

PGM 2020 Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting

ICML 2020 Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van Den Broeck, Kristian Kersting, Zoubin Ghahramani

ICLR 2020 From Variational to Deterministic Autoencoders Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael Black, Bernhard Schölkopf

ICMLW 2020 Handling Missing Data in Decision Trees: A Probabilistic Approach Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck

NeurIPS 2020 Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck

ICML 2020 Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van Den Broeck

PGM 2020 Strudel: Learning Structured-Decomposable Probabilistic Circuits Meihua Dang, Antonio Vergari, Guy Broeck

AAAI 2019 Automatic Bayesian Density Analysis Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera

NeurIPS 2019 On Tractable Computation of Expected Predictions Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck

UAI 2019 Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Xiaoting Shao, Martin Trapp, Kristian Kersting, Zoubin Ghahramani

MLJ 2019 Visualizing and Understanding Sum-Product Networks Antonio Vergari, Nicola Di Mauro, Floriana Esposito

AAAI 2018 Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting

AAAI 2018 Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks Antonio Vergari, Robert Peharz, Nicola Di Mauro, Alejandro Molina, Kristian Kersting, Floriana Esposito

ICLR 2017 Encoding and Decoding Representations with Sum- and Max-Product Networks Antonio Vergari, Robert Peharz, Nicola Di Mauro, Floriana Esposito

ECML-PKDD 2017 Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks Nicola Di Mauro, Antonio Vergari, Teresa Maria Altomare Basile, Floriana Esposito

PGM 2016 Multi-Label Classification with Cutset Networks Nicola Di Mauro, Antonio Vergari, Floriana Esposito

ECML-PKDD 2015 Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning Antonio Vergari, Nicola Di Mauro, Floriana Esposito