Antonio Vergari
33 papers · 2016–2025 · 13 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+14 more ↓ Show less ↑
π Conference Polyglot (13) π Academic Marathon (9) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (13)
π
Cross-Pollinator
(13)
π
Renaissance Researcher
(7)
πΊοΈ
Taxonomy Completionist
(43)
π
Keyword Champion
(2)
π¬
Deep Specialist
(11)
π
Triple Crown
π
Grand Slam
π
Conference Pioneer
ποΈ
Keyword Collector
(112)
π
Century Club
(33)
β‘
Prolific Year
(7)
β
The Questioner
(3)
π₯
Unstoppable
(7)
π
Trend Setter
Conferences
NIPS (8)
AAAI (4)
ICML (4)
UAI (4)
ICLR (3)
PGM (3)
ACL (1)
AISTATS (1)
COLING (1)
EACL (1)
EMNLP (1)
MLHC (1)
NAACL (1)
Top co-authors
Keywords
probabilistic circuit
(8)
probabilistic inference
(6)
generative model
(6)
exact inference
(3)
zero-shot learning
(3)
sum-product network
(3)
benchmark evaluation
(2)
variational inference
(2)
numerical quadrature
(2)
density estimation
(2)
structure learning
(2)
probabilistic modeling
(2)
tractable inference
(2)
continuous latent variable
(2)
multi-label classification
(2)
link prediction
(2)
message passing
(2)
anomaly detection
(2)
concept learning
(2)
probabilistic model
(2)
Papers
A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction
UAI 2025
Sum of Squares Circuits
AAAI 2025
SEMMA: A Semantic Aware Knowledge Graph Foundation Model
EMNLP 2025
Logically Consistent Language Models via Neuro-Symbolic Integration
ICLR 2025
Is Complex Query Answering Really Complex?
ICML 2025
Can interpretability and accuracy coexist in cancer survival analysis?
MLHC 2025
What can Large Language Models Capture about Code Functional Equivalence?
NAACL 2025
A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts
NIPS 2024
Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification
AAAI 2024
PIXAR: Auto-Regressive Language Modeling in Pixel Space
ACL 2024
Probabilistic Integral Circuits
AISTATS 2024
Subtractive Mixture Models via Squaring: Representation and Learning
ICLR 2024
On the Independence Assumption in Neurosymbolic Learning
ICML 2024
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts
UAI 2024
Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits
NIPS 2024
How to Turn Your Knowledge Graph Embeddings into Generative Models
NIPS 2023
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
NIPS 2023
Semantic Probabilistic Layers for Neuro-Symbolic Learning
NIPS 2022
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games
EACL 2021
Tractable computation of expected kernels
UAI 2021
Juice: A Julia Package for Logic and Probabilistic Circuits
AAAI 2021
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference
NIPS 2021
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing
ICML 2020
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations
NIPS 2020
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures
PGM 2020
Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games
COLING 2020
Strudel: Learning Structured-Decomposable Probabilistic Circuits
PGM 2020
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
ICML 2020
From Variational to Deterministic Autoencoders
ICLR 2020
On Tractable Computation of Expected Predictions
NIPS 2019
Automatic Bayesian Density Analysis
AAAI 2019
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
UAI 2019
Multi-Label Classification with Cutset Networks
PGM 2016