default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDAntonio Vergari
Person information
- affiliation: University of Edinburgh, UK
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j6]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo
:
From MNIST to ImageNet and back: benchmarking continual curriculum learning. Mach. Learn. 113(10): 8137-8164 (2024)- [c36]Andreas Grivas, Antonio Vergari, Adam Lopez:
Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification. AAAI 2024: 12208-12216 - [c35]Yintao Tai, Xiyang Liao, Alessandro Suglia, Antonio Vergari:
PIXAR: Auto-Regressive Language Modeling in Pixel Space. ACL (Findings) 2024: 14673-14695 - [c34]Gennaro Gala, Cassio P. de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur:
Probabilistic Integral Circuits. AISTATS 2024: 2143-2151 - [c33]Lorenzo Loconte, Aleksanteri M. Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari:
Subtractive Mixture Models via Squaring: Representation and Learning. ICLR 2024 - [c32]Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari:
On the Independence Assumption in Neurosymbolic Learning. ICML 2024 - [c31]Andrea Valenti, Davide Bacciu, Antonio Vergari:
ChemAlgebra: Algebraic Reasoning on Chemical Reactions. IJCNN 2024: 1-8 - [i40]Yintao Tai, Xiyang Liao, Alessandro Suglia, Antonio Vergari:
PIXAR: Auto-Regressive Language Modeling in Pixel Space. CoRR abs/2401.03321 (2024) - [i39]Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso:
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts. CoRR abs/2402.12240 (2024) - [i38]Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari:
On the Independence Assumption in Neurosymbolic Learning. CoRR abs/2404.08458 (2024) - [i37]Diego Calanzone, Stefano Teso, Antonio Vergari:
Towards Logically Consistent Language Models via Probabilistic Reasoning. CoRR abs/2404.12843 (2024) - [i36]Gennaro Gala, Cassio de Campos, Antonio Vergari, Erik Quaeghebeur:
Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits. CoRR abs/2406.06494 (2024) - [i35]Samuele Bortolotti, Emanuele Marconato, Tommaso Carraro, Paolo Morettin, Emile van Krieken, Antonio Vergari, Stefano Teso, Andrea Passerini:
A Benchmark Suite for Systematically Evaluating Reasoning Shortcuts. CoRR abs/2406.10368 (2024) - [i34]Nickil Maveli, Antonio Vergari, Shay B. Cohen:
What can Large Language Models Capture about Code Functional Equivalence? CoRR abs/2408.11081 (2024) - [i33]Lorenzo Loconte, Stefan Mengel, Antonio Vergari:
Sum of Squares Circuits. CoRR abs/2408.11778 (2024) - [i32]Lorenzo Loconte, Antonio Mari, Gennaro Gala, Robert Peharz, Cassio de Campos, Erik Quaeghebeur, Gennaro Vessio, Antonio Vergari:
What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)? CoRR abs/2409.07953 (2024) - [i31]Diego Calanzone, Stefano Teso, Antonio Vergari:
Logically Consistent Language Models via Neuro-Symbolic Integration. CoRR abs/2409.13724 (2024) - 2023
- [c30]Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari:
Semantic Probabilistic Layers for Neuro-Symbolic Learning. NeSy 2023: 413 - [c29]Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari:
How to Turn Your Knowledge Graph Embeddings into Generative Models. NeurIPS 2023 - [c28]Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini:
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts. NeurIPS 2023 - [i30]Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo:
From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning. CoRR abs/2303.11076 (2023) - [i29]Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari:
How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits. CoRR abs/2305.15944 (2023) - [i28]Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini:
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts. CoRR abs/2305.19951 (2023) - [i27]Aryo Pradipta Gema, Dominik Grabarczyk, Wolf De Wulf, Piyush Borole, Javier Antonio Alfaro, Pasquale Minervini, Antonio Vergari, Ajitha Rajan:
Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy Tasks. CoRR abs/2305.19979 (2023) - [i26]Lorenzo Loconte, Aleksanteri M. Sladek, Stefan Mengel, Martin Trapp, Arno Solin, Nicolas Gillis, Antonio Vergari:
Subtractive Mixture Models via Squaring: Representation and Learning. CoRR abs/2310.00724 (2023) - [i25]Andreas Grivas, Antonio Vergari, Adam Lopez:
Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification. CoRR abs/2310.10443 (2023) - [i24]Gennaro Gala, Cassio P. de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur:
Probabilistic Integral Circuits. CoRR abs/2310.16986 (2023) - [i23]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:
Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning. CoRR abs/2311.04215 (2023) - 2022
- [j5]Meihua Dang, Antonio Vergari, Guy Van den Broeck:
Strudel: A fast and accurate learner of structured-decomposable probabilistic circuits. Int. J. Approx. Reason. 140: 92-115 (2022) - [j4]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. 140: 298-313 (2022) - [c27]Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari:
Semantic Probabilistic Layers for Neuro-Symbolic Learning. NeurIPS 2022 - [i22]Stefano Teso, Antonio Vergari:
Efficient and Reliable Probabilistic Interactive Learning with Structured Outputs. CoRR abs/2202.08566 (2022) - [i21]Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari:
Semantic Probabilistic Layers for Neuro-Symbolic Learning. CoRR abs/2206.00426 (2022) - [i20]Andrea Valenti, Davide Bacciu, Antonio Vergari:
ChemAlgebra: Algebraic Reasoning on Chemical Reactions. CoRR abs/2210.02095 (2022) - [i19]Priyank Jaini, Kristian Kersting, Antonio Vergari, Max Welling:
Recent Advancements in Tractable Probabilistic Inference (Dagstuhl Seminar 22161). Dagstuhl Reports 12(4): 13-25 (2022) - 2021
- [c26]Meihua Dang, Pasha Khosravi, Yitao Liang, Antonio Vergari, Guy Van den Broeck:
Juice: A Julia Package for Logic and Probabilistic Circuits. AAAI 2021: 16020-16023 - [c25]Agnieszka Dobrowolska, Antonio Vergari, Pasquale Minervini:
Neural Concept Formation in Knowledge Graphs. AKBC 2021 - [c24]Alessandro Suglia, Yonatan Bisk, Ioannis Konstas, Antonio Vergari, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon:
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games. EACL 2021: 2135-2144 - [c23]Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck:
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference. NeurIPS 2021: 13189-13201 - [c22]Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck:
Tractable computation of expected kernels. UAI 2021: 1163-1173 - [i18]Alessandro Suglia, Yonatan Bisk, Ioannis Konstas, Antonio Vergari, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon:
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games. CoRR abs/2102.00424 (2021) - [i17]Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck:
A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries. CoRR abs/2102.06137 (2021) - [i16]Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck:
Tractable Computation of Expected Kernels by Circuits. CoRR abs/2102.10562 (2021) - 2020
- [c21]Alessandro Suglia, Antonio Vergari, Ioannis Konstas, Yonatan Bisk, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon:
Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games. COLING 2020: 1090-1102 - [c20]Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schölkopf:
From Variational to Deterministic Autoencoders. ICLR 2020 - [c19]Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani:
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML 2020: 7563-7574 - [c18]Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck:
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing. ICML 2020: 10990-11000 - [c17]Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck:
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations. NeurIPS 2020 - [c16]Meihua Dang, Antonio Vergari, Guy Van den Broeck:
Strudel: Learning Structured-Decomposable Probabilistic Circuits. PGM 2020: 137-148 - [c15]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM 2020: 401-412 - [i15]Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck:
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing. CoRR abs/2003.00126 (2020) - [i14]Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani:
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. CoRR abs/2004.06231 (2020) - [i13]Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck:
Handling Missing Data in Decision Trees: A Probabilistic Approach. CoRR abs/2006.16341 (2020) - [i12]Meihua Dang, Antonio Vergari, Guy Van den Broeck:
Strudel: Learning Structured-Decomposable Probabilistic Circuits. CoRR abs/2007.09331 (2020) - [i11]Alessandro Suglia, Antonio Vergari, Ioannis Konstas, Yonatan Bisk, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon:
Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games. CoRR abs/2011.02917 (2020)
2010 – 2019
- 2019
- [j3]Teresa Maria Altomare Basile, Nicola Di Mauro, Floriana Esposito, Stefano Ferilli, Antonio Vergari:
Ensembles of density estimators for positive-unlabeled learning. J. Intell. Inf. Syst. 53(2): 199-217 (2019) - [j2]Antonio Vergari, Nicola Di Mauro, Floriana Esposito:
Visualizing and understanding Sum-Product Networks. Mach. Learn. 108(4): 551-573 (2019) - [c14]Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera:
Automatic Bayesian Density Analysis. AAAI 2019: 5207-5215 - [c13]Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck:
On Tractable Computation of Expected Predictions. NeurIPS 2019: 11167-11178 - [c12]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani:
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI 2019: 334-344 - [i10]Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting:
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR abs/1901.03704 (2019) - [i9]Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael J. Black, Bernhard Schölkopf:
From Variational to Deterministic Autoencoders. CoRR abs/1903.12436 (2019) - [i8]Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting:
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR abs/1905.08550 (2019) - [i7]Zhe Zeng, Fanqi Yan, Paolo Morettin, Antonio Vergari, Guy Van den Broeck:
Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message Passing. CoRR abs/1909.09362 (2019) - [i6]Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck:
On Tractable Computation of Expected Predictions. CoRR abs/1910.02182 (2019) - 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) - [c11]Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting:
Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains. AAAI 2018: 3828-3835 - [c10]Antonio Vergari, Robert Peharz, Nicola Di Mauro, Alejandro Molina, Kristian Kersting, Floriana Esposito:
Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks. AAAI 2018: 4163-4170 - [i5]Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani:
Probabilistic Deep Learning using Random Sum-Product Networks. CoRR abs/1806.01910 (2018) - [i4]Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera:
Automatic Bayesian Density Analysis. CoRR abs/1807.09306 (2018) - 2017
- [c9]Nicola Di Mauro, Floriana Esposito, Fabrizio Giuseppe Ventola, Antonio Vergari:
Alternative Variable Splitting Methods to Learn Sum-Product Networks. AI*IA 2017: 334-346 - [c8]Antonio Vergari, Robert Peharz, Nicola Di Mauro, Floriana Esposito:
Encoding and Decoding Representations with Sum- and Max-Product Networks. ICLR (Workshop) 2017 - [c7]Teresa Maria Altomare Basile, Nicola Di Mauro, Floriana Esposito, Stefano Ferilli, Antonio Vergari:
Density Estimators for Positive-Unlabeled Learning. NFMCP@PKDD/ECML 2017: 49-64 - [c6]Nicola Di Mauro, Antonio Vergari, Teresa Maria Altomare Basile, Floriana Esposito:
Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks. ECML/PKDD (1) 2017: 203-219 - [c5]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 - [i3]Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting:
Sum-Product Networks for Hybrid Domains. CoRR abs/1710.03297 (2017) - 2016
- [c4]Nicola Di Mauro, Antonio Vergari, Floriana Esposito:
Multi-Label Classification with Cutset Networks. Probabilistic Graphical Models 2016: 147-158 - [i2]Antonio Vergari, Nicola Di Mauro, Floriana Esposito:
Towards Representation Learning with Tractable Probabilistic Models. CoRR abs/1608.02341 (2016) - [i1]Antonio Vergari, Nicola Di Mauro, Floriana Esposito:
Visualizing and Understanding Sum-Product Networks. CoRR abs/1608.08266 (2016) - 2015
- [c3]Nicola Di Mauro, Antonio Vergari, Floriana Esposito:
Learning Accurate Cutset Networks by Exploiting Decomposability. AI*IA 2015: 221-232 - [c2]Nicola Di Mauro, Antonio Vergari, Teresa Maria Altomare Basile:
Learning Bayesian Random Cutset Forests. ISMIS 2015: 122-132 - [c1]Antonio Vergari, Nicola Di Mauro, Floriana Esposito:
Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning. ECML/PKDD (2) 2015: 343-358
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-07 21:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
