← Authors

Guy Van den Broeck

75 papers · 2013–2026 · 11 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (22) 🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (12) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10) πŸ”¬ Deep Specialist (28) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam 🀝 Dynamic Duo (13) ❓ The Questioner (2) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (11) ⚑ Prolific Year (8) πŸ—ƒοΈ Keyword Collector (53) πŸ’Ž Century Club (74)

Conferences

NIPS (19) IJCAI (13) ICML (10) AAAI (9) ICLR (8) AISTATS (6) UAI (6) ACL (1) CORL (1) EACL (1) EMNLP (1)

Top co-authors

Anji Liu (13) Kareem Ahmed (11) YooJung Choi (10) Honghua Zhang (10) Yitao Liang (9) Zhe Zeng (8) Antonio Vergari (8) Kai-Wei Chang (7) Mathias Niepert (6) Benjie Wang (6)

Keywords

probabilistic inference (14) probabilistic circuit (13) graphical model (7) tractable inference (7) probabilistic modeling (5) generative model (5) neuro-symbolic learning (4) density estimation (4) bayesian network (4) exact inference (4) constraint satisfaction (4) lifted inference (4) probabilistic graphical model (4) parameter learning (3) autoregressive model (3) weighted model integration (3) variational inference (3) feature selection (3) probabilistic model (3) logical constraint (3)

Papers

Enabling Autoregressive Models to Fill In Masked Tokens EACL 2026
TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation ICML 2025
Learning to Discretize Denoising Diffusion ODEs ICLR 2025
Discrete Copula Diffusion ICLR 2025
Restructuring Tractable Probabilistic Circuits AISTATS 2025
Controllable Generation via Locally Constrained Resampling ICLR 2025
Tractable Transformers for Flexible Conditional Generation ICML 2025
The Limits of Tractable Marginalization ICML 2025
On the Relationship Between Monotone and Squared Probabilistic Circuits AAAI 2025
Adversarial Tokenization ACL 2025
Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models AISTATS 2025
Scaling Probabilistic Circuits via Monarch Matrices ICML 2025
Scaling Tractable Probabilistic Circuits: A Systems Perspective ICML 2024
Polynomial Semantics of Tractable Probabilistic Circuits UAI 2024
Where is the signal in tokenization space? EMNLP 2024
Image Inpainting via Tractable Steering of Diffusion Models ICLR 2024
A Tractable Inference Perspective of Offline RL NIPS 2024
Adaptable Logical Control for Large Language Models NIPS 2024
A Compositional Atlas for Algebraic Circuits NIPS 2024
Probabilistically Rewired Message-Passing Neural Networks ICLR 2024
SIMPLE: A Gradient Estimator for k-Subset Sampling ICLR 2023
On the Paradox of Learning to Reason from Data IJCAI 2023
A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints NIPS 2023
A Unified Approach to Count-Based Weakly Supervised Learning NIPS 2023
Collapsed Inference for Bayesian Deep Learning NIPS 2023
Tractable Control for Autoregressive Language Generation ICML 2023
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits ICML 2023
Scaling integer arithmetic in probabilistic programs UAI 2023
Out-of-Distribution Generalization by Neural-Symbolic Joint Training AAAI 2023
Certifying Fairness of Probabilistic Circuits AAAI 2023
Semantic Strengthening of Neuro-Symbolic Learning AISTATS 2023
Mixtures of All Trees AISTATS 2023
Scaling Up Probabilistic Circuits by Latent Variable Distillation ICLR 2023
Lossless Compression with Probabilistic Circuits ICLR 2022
Neuro-symbolic entropy regularization UAI 2022
Semantic Probabilistic Layers for Neuro-Symbolic Learning NIPS 2022
PYLON: A PyTorch Framework for Learning with Constraints AAAI 2022
Solving Marginal MAP Exactly by Probabilistic Circuit Transformations AISTATS 2022
Sparse Probabilistic Circuits via Pruning and Growing NIPS 2022
Tractable Regularization of Probabilistic Circuits NIPS 2021
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference NIPS 2021
On the Tractability of SHAP Explanations AAAI 2021
Group Fairness by Probabilistic Modeling with Latent Fair Decisions AAAI 2021
Juice: A Julia Package for Logic and Probabilistic Circuits AAAI 2021
Probabilistic Generating Circuits ICML 2021
Probabilistic Sufficient Explanations IJCAI 2021
Tractable computation of expected kernels UAI 2021
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits ICML 2020
SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning CORL 2020
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing ICML 2020
Counterexample-Guided Learning of Monotonic Neural Networks NIPS 2020
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations NIPS 2020
Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns AAAI 2020
Towards Hardware-Aware Tractable Learning of Probabilistic Models NIPS 2019
What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features IJCAI 2019
On Constrained Open-World Probabilistic Databases IJCAI 2019
Learning Logistic Circuits AAAI 2019
On Tractable Computation of Expected Predictions NIPS 2019
Smoothing Structured Decomposable Circuits NIPS 2019
Generating and Sampling Orbits for Lifted Probabilistic Inference UAI 2019
Efficient Search-Based Weighted Model Integration UAI 2019
Approximate Knowledge Compilation by Online Collapsed Importance Sampling NIPS 2018
On Robust Trimming of Bayesian Network Classifiers IJCAI 2018
Optimal Feature Selection for Decision Robustness in Bayesian Networks IJCAI 2017
Open-World Probabilistic Databases: An Abridged Report IJCAI 2017
Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report IJCAI 2016
New Liftable Classes for First-Order Probabilistic Inference NIPS 2016
First-Order Model Counting in a Nutshell IJCAI 2016
Probabilistic Inference in Hybrid Domains by Weighted Model Integration IJCAI 2015
Tractable Learning for Structured Probability Spaces: A Case Study in Learning Preference Distributions IJCAI 2015
Tractable Learning for Complex Probability Queries NIPS 2015
Anytime Inference in Probabilistic Logic Programs with Tp-Compilation IJCAI 2015
Inducing Probabilistic Relational Rules from Probabilistic Examples IJCAI 2015
On the Complexity and Approximation of Binary Evidence in Lifted Inference NIPS 2013
Completeness Results for Lifted Variable Elimination AISTATS 2013