Vergari, Antonio
- Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
2023/05/31 by Emanuele Marconato, Stefano Teso, Marconato, Emanuele +5 · 2 voices · 8 citations
#cs.LG #stat.ML
- Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic\n Circuits
2020/04/13 by Robert Peharz, Steven Lang, Peharz, Robert +15 · 9 citations
Computer Science · #Advanced Neural Network Applications #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- From Variational to Deterministic Autoencoders
2019/03/29 by Partha Ghosh, Ghosh, Partha, Mehdi S. M. Sajjadi +7 · 9 citations
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
- Semantic Probabilistic Layers for Neuro-Symbolic Learning
2022/06/01 by Kareem Ahmed, Stefano Teso, Ahmed, Kareem +7 · 9 citations
Computer Science · #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Neural Networks and Applications
- Subtractive Mixture Models via Squaring: Representation and Learning
2023/10/01 by Lorenzo Loconte, Aleksanteri M. Sladek, Aleksanteri Sladek +12 · 2 voices · 7 citations
Computer Science · #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Bayesian Methods and Mixture Models
- Logically Consistent Language Models via Neuro-Symbolic Integration
2024/09/09 by Diego Calanzone, Stefano Teso, Calanzone, Diego +3 · 2 voices · 4 citations
Computer Science · #Natural Language Processing Techniques #Topic Modeling
- SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks
2019/01/11 by Molina, Alejandro, Vergari, Antonio, Stelzner, Karl +5 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- What can Large Language Models Capture about Code Functional Equivalence?
2024/08/20 by Nickil Maveli, Antonio Vergari, Maveli, Nickil +3 · 5 citations
Computer Science · #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
- Conditional Sum-Product Networks: Imposing Structure on Deep\n Probabilistic Architectures
2019/05/21 by Xiaoting Shao, Alejandro Molina, Shao, Xiaoting +11 · 2 citations
Business, Management and Accounting · Computer Science · #Bayesian Modeling and Causal Inference #Computational Drug Discovery Methods #FOS: Computer and information sciences #Graph Theory and Algorithms #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Product Development and Customization
- A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts
2024/06/14 by Bortolotti, Samuele, Marconato, Emanuele, Carraro, Tommaso +5 · 4 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- PIXAR: Auto-Regressive Language Modeling in Pixel Space
2024/01/06 by Yintao Tai, Xiyang Liao, Tai, Yintao +5 · 3 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
- Is Complex Query Answering Really Complex?
2024/10/16 by Cosimo Gregucci, Gregucci, Cosimo, Bo Xiong +11 · 2 voices · 2 citations
#cs.LG #cs.AI
- BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts
2024/02/19 by Marconato, Emanuele, Bortolotti, Samuele, van Krieken, Emile +3 · 2 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Sum of Squares Circuits
2024/08/21 by Lorenzo Loconte, Loconte, Lorenzo, Stefan Mengel +3 · 2 voices · 2 citations
Computer Science · #Neural Networks and Applications #Numerical Methods and Algorithms
- How to Turn Your Knowledge Graph Embeddings into Generative Models
2023/05/25 by Lorenzo Loconte, Nicola Di Mauro, Loconte, Lorenzo +5 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Bioinformatics and Genomic Networks #Complex Network Analysis Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG)
- On Tractable Computation of Expected Predictions
2019/10/05 by Khosravi, Pasha, Choi, YooJung, Liang, Yitao +2 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- SEMMA: A Semantic Aware Knowledge Graph Foundation Model
2025/05/26 by Arvindh Arun, Sumit Kumar, Arun, Arvindh +11 · 3 citations
Computer Science · Decision Sciences · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Data Quality and Management #FOS: Computer and information sciences #Semantic Web and Ontologies
- Neurosymbolic Diffusion Models
2025/05/19 by Emile van Krieken, Pasquale Minervini, van Krieken, Emile +5 · 1 voice · 1 citation
#cs.LG
- From MNIST to ImageNet and Back: Benchmarking Continual Curriculum Learning
2023/03/16 by Kamil Faber, Faber, Kamil, Dominik Żurek +9 · 1 citation
Computer Science · Medicine · #Artificial Intelligence (cs.AI) #COVID-19 diagnosis using AI #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
- Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy Tasks
2023/05/31 by Gema, Aryo Pradipta, Grabarczyk, Dominik, De Wulf, Wolf +5 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Imagining Grounded Conceptual Representations from Perceptual\n Information in Situated Guessing Games
2020/11/05 by Alessandro Suglia, Antonio Vergari, Suglia, Alessandro +11 · 1 citation
Computer Science · #Artificial Intelligence in Games #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
- Probabilistic Integral Circuits
2023/10/25 by Gala, Gennaro, de Campos, Cassio, Peharz, Robert +2 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Symbol Grounding in Neuro-Symbolic AI: A Gentle Introduction to Reasoning Shortcuts
2025/10/16 by Marconato, Emanuele, Bortolotti, Samuele, van Krieken, Emile +6 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)