Antonio Vergari

Affiliations

University of Edinburgh

papers

269

total citations

papers (10)

Semantic Probabilistic Layers for Neuro-Symbolic Learning

NEURIPS 2022arXiv

107

citations

Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

NEURIPS 2023arXiv

citations

Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification

AAAI 2024arXiv

citations

Neurosymbolic Diffusion Models

NEURIPS 2025arXiv

citations

A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference

NEURIPS 2021

citations

Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations

NEURIPS 2020

citations

Antonio Vergari

Affiliations

papers (10)

Semantic Probabilistic Layers for Neuro-Symbolic Learning

Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

Subtractive Mixture Models via Squaring: Representation and Learning

How to Turn Your Knowledge Graph Embeddings into Generative Models

On the Independence Assumption in Neurosymbolic Learning

Sum of Squares Circuits

Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification

Neurosymbolic Diffusion Models

A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference

Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations

papers (10)

Semantic Probabilistic Layers for Neuro-Symbolic Learning

Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

Subtractive Mixture Models via Squaring: Representation and Learning

How to Turn Your Knowledge Graph Embeddings into Generative Models

On the Independence Assumption in Neurosymbolic Learning

Sum of Squares Circuits

Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification

Neurosymbolic Diffusion Models

A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference

Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations