Guy Van den Broeck

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 179

Top Venues

Katholieke Universiteit Leuven, Belgium (PHD)

Education History

Katholieke Universiteit Leuven, Belgium

PHD

Publications

Oliver Broadrick, Honghua Zhang, Guy Van den Broeck
Polynomial Semantics of Tractable Probabilistic Circuits. CoRR (2024)
Anji Liu, Mathias Niepert, Guy Van den Broeck
Image Inpainting via Tractable Steering of Diffusion Models. ICLR (2024)
Vinh Tong, Anji Liu, Trung-Dung Hoang, Guy Van den Broeck, Mathias Niepert
Learning to Discretize Denoising Diffusion ODEs. CoRR (2024)
Anji Liu, Mathias Niepert, Guy Van den Broeck
Image Inpainting via Tractable Steering of Diffusion Models. CoRR (2024)
Siyan Zhao, Daniel Israel, Guy Van den Broeck, Aditya Grover
Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models. CoRR (2024)
Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris
Probabilistically Rewired Message-Passing Neural Networks. ICLR (2024)
Honghua Zhang, Po-Nien Kung, Masahiro Yoshida, Guy Van den Broeck, Nanyun Peng
Adaptable Logical Control for Large Language Models. CoRR (2024)
Poorva Garg, Steven Holtzen, Guy Van den Broeck, Todd D. Millstein
Bit Blasting Probabilistic Programs. Proc. ACM Program. Lang. 8 (PLDI) (2024)
Antoine Amarilli, Marcelo Arenas, YooJung Choi, Mikaël Monet, Guy Van den Broeck, Benjie Wang
A Circus of Circuits: Connections Between Decision Diagrams, Circuits, and Automata. CoRR (2024)
Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin
On the Challenges and Opportunities in Generative AI. CoRR (2024)
Anji Liu, Kareem Ahmed, Guy Van den Broeck
Scaling Tractable Probabilistic Circuits: A Systems Perspective. CoRR (2024)
Kareem Ahmed, Stefano Teso, Paolo Morettin, Luca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Yitao Liang, Eric Wang, Kai-Wei Chang, Andrea Passerini, Guy Van den Broeck
Semantic Loss Functions for Neuro-Symbolic Structured Prediction. CoRR (2024)
Poorva Garg, Steven Holtzen, Guy Van den Broeck, Todd D. Millstein
Bit Blasting Probabilistic Programs. CoRR (2023)
Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits. ICML (2023)
Nikil Roashan Selvam, Honghua Zhang, Guy Van den Broeck
Mixtures of All Trees. CoRR (2023)
William X. Cao, Poorva Garg, Ryan Tjoa, Steven Holtzen, Todd D. Millstein, Guy Van den Broeck
Scaling Integer Arithmetic in Probabilistic Programs. CoRR (2023)
Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck
Semantic Strengthening of Neuro-Symbolic Learning. CoRR (2023)
Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris
Probabilistically Rewired Message-Passing Neural Networks. CoRR (2023)
Honghua Zhang, Meihua Dang, Nanyun Peng, Guy Van den Broeck
Tractable Control for Autoregressive Language Generation. CoRR (2023)
Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits. CoRR (2023)
Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
Semantic Probabilistic Layers for Neuro-Symbolic Learning. NeSy (2023)
Honghua Zhang, Meihua Dang, Nanyun Peng, Guy Van den Broeck
Tractable Control for Autoregressive Language Generation. ICML (2023)
Daniel Israel, Aditya Grover, Guy Van den Broeck
High Dimensional Causal Inference with Variational Backdoor Adjustment. CoRR (2023)
William X. Cao, Poorva Garg, Ryan Tjoa, Steven Holtzen, Todd D. Millstein, Guy Van den Broeck
Scaling integer arithmetic in probabilistic programs. UAI (2023)
Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck
A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints. CoRR (2023)
Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang
Expressive Modeling Is Insufficient for Offline RL: A Tractable Inference Perspective. CoRR (2023)
Nikil Roashan Selvam, Honghua Zhang, Guy Van den Broeck
Mixtures of All Trees. AISTATS (2023)
Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck
SIMPLE: A Gradient Estimator for k-Subset Sampling. ICLR (2023)
Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck
A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints. NeurIPS (2023)
Nikil Roashan Selvam, Guy Van den Broeck, YooJung Choi
Certifying Fairness of Probabilistic Circuits. AAAI (2023)
Zhe Zeng, Guy Van den Broeck
Collapsed Inference for Bayesian Deep Learning. NeurIPS (2023)
Vinay Shukla, Zhe Zeng, Kareem Ahmed, Guy Van den Broeck
A Unified Approach to Count-Based Weakly-Supervised Learning. CoRR (2023)
Zhe Zeng, Guy Van den Broeck
Collapsed Inference for Bayesian Deep Learning. CoRR (2023)
Sebastian Junges, Joost-Pieter Katoen, Scott Sanner, Guy Van den Broeck, Bahare Salmani
Scalable Analysis of Probabilistic Models and Programs (Dagstuhl Seminar 23241). Dagstuhl Reports 13 (6) (2023)
Honghua Zhang, Liunian Harold Li, Tao Meng, Kai-Wei Chang, Guy Van den Broeck
On the Paradox of Learning to Reason from Data. IJCAI (2023)
Anji Liu, Hongming Xu, Guy Van den Broeck, Yitao Liang
Out-of-Distribution Generalization by Neural-Symbolic Joint Training. AAAI (2023)
Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck
Semantic Strengthening of Neuro-Symbolic Learning. AISTATS (2023)
Anji Liu, Honghua Zhang, Guy Van den Broeck
Scaling Up Probabilistic Circuits by Latent Variable Distillation. ICLR (2023)
Vinay Shukla, Zhe Zeng, Kareem Ahmed, Guy Van den Broeck
A Unified Approach to Count-Based Weakly Supervised Learning. NeurIPS (2023)
YooJung Choi, Tal Friedman, Guy Van den Broeck
Solving Marginal MAP Exactly by Probabilistic Circuit Transformations. AISTATS (2022)
Meihua Dang, Anji Liu, Xinzhu Wei, Sriram Sankararaman, Guy Van den Broeck
Tractable and Expressive Generative Models of Genetic Variation Data. RECOMB (2022)
Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
Semantic Probabilistic Layers for Neuro-Symbolic Learning. CoRR (2022)
Meihua Dang, Antonio Vergari, Guy Van den Broeck
Strudel: A fast and accurate learner of structured-decomposable probabilistic circuits. Int. J. Approx. Reason. 140 (2022)
Kareem Ahmed, Tao Li, Thy Ton, Quan Guo, Kai-Wei Chang, Parisa Kordjamshidi, Vivek Srikumar, Guy Van den Broeck, Sameer Singh
PYLON: A PyTorch Framework for Learning with Constraints. AAAI (2022)
Anji Liu, Honghua Zhang, Guy Van den Broeck
Scaling Up Probabilistic Circuits by Latent Variable Distillation. CoRR (2022)
Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari
Semantic Probabilistic Layers for Neuro-Symbolic Learning. NeurIPS (2022)
Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck
Neuro-symbolic entropy regularization. UAI (2022)
Anji Liu, Stephan Mandt, Guy Van den Broeck
Lossless Compression with Probabilistic Circuits. ICLR (2022)
Meihua Dang, Anji Liu, Guy Van den Broeck
Sparse Probabilistic Circuits via Pruning and Growing. CoRR (2022)
Meihua Dang, Anji Liu, Guy Van den Broeck
Sparse Probabilistic Circuits via Pruning and Growing. NeurIPS (2022)
Nikil Roashan Selvam, Guy Van den Broeck, YooJung Choi
Certifying Fairness of Probabilistic Circuits. CoRR (2022)
Honghua Zhang, Liunian Harold Li, Tao Meng, Kai-Wei Chang, Guy Van den Broeck
On the Paradox of Learning to Reason from Data. CoRR (2022)
Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck
SIMPLE: A Gradient Estimator for k-Subset Sampling. CoRR (2022)
Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu
On the Tractability of SHAP Explanations. J. Artif. Intell. Res. 74 (2022)
Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck
Neuro-Symbolic Entropy Regularization. CoRR (2022)
Ismail Ilkan Ceylan, Adnan Darwiche, Guy Van den Broeck
Open-world probabilistic databases: Semantics, algorithms, complexity. Artif. Intell. 295 (2021)
Anji Liu, Stephan Mandt, Guy Van den Broeck
Lossless Compression with Probabilistic Circuits. CoRR (2021)
Honghua Zhang, Brendan Juba, Guy Van den Broeck
Probabilistic Generating Circuits. ICML (2021)
Yipeng Huang, Steven Holtzen, Todd D. Millstein, Guy Van den Broeck, Margaret Martonosi
Logical abstractions for noisy variational Quantum algorithm simulation. ASPLOS (2021)
Eric Wang, Pasha Khosravi, Guy Van den Broeck
Probabilistic Sufficient Explanations. CoRR (2021)
Kareem Ahmed, Tao Li, Thy Ton, Quan Guo, Kai-Wei Chang, Parisa Kordjamshidi, Vivek Srikumar, Guy Van den Broeck, Sameer Singh
Pylon: A PyTorch Framework for Learning with Constraints. NeurIPS (Competition and Demos) (2021)
Steven Holtzen, Sebastian Junges, Marcell Vazquez-Chanlatte, Todd D. Millstein, Sanjit A. Seshia, Guy Van den Broeck
Model Checking Finite-Horizon Markov Chains with Probabilistic Inference. CAV (2) (2021)
YooJung Choi, Tal Friedman, Guy Van den Broeck
Solving Marginal MAP Exactly by Probabilistic Circuit Transformations. CoRR (2021)
Yipeng Huang, Steven Holtzen, Todd D. Millstein, Guy Van den Broeck, Margaret Martonosi
Logical Abstractions for Noisy Variational Quantum Algorithm Simulation. CoRR (2021)
YooJung Choi, Meihua Dang, Guy Van den Broeck
Group Fairness by Probabilistic Modeling with Latent Fair Decisions. AAAI (2021)
Yu-Hsi Cheng, Todd D. Millstein, Guy Van den Broeck, Steven Holtzen
flip-hoisting: Exploiting Repeated Parameters in Discrete Probabilistic Programs. CoRR (2021)
Rushil Gupta, Vishal Sharma, Yash Jain, Yitao Liang, Guy Van den Broeck, Parag Singla
Towards an Interpretable Latent Space in Structured Models for Video Prediction. CoRR (2021)
Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck
Tractable Computation of Expected Kernels by Circuits. CoRR (2021)
Eric Wang, Pasha Khosravi, Guy Van den Broeck
Probabilistic Sufficient Explanations. IJCAI (2021)
Meihua Dang, Pasha Khosravi, Yitao Liang, Antonio Vergari, Guy Van den Broeck
Juice: A Julia Package for Logic and Probabilistic Circuits. AAAI (2021)
Steven Holtzen, Sebastian Junges, Marcell Vazquez-Chanlatte, Todd D. Millstein, Sanjit A. Seshia, Guy Van den Broeck
Model Checking Finite-Horizon Markov Chains with Probabilistic Inference. CoRR (2021)
Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference. NeurIPS (2021)
Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu
On the Tractability of SHAP Explanations. AAAI (2021)
Wenzhe Li, Zhe Zeng, Antonio Vergari, Guy Van den Broeck
Tractable computation of expected kernels. UAI (2021)
Guy Van den Broeck
From Probabilistic Circuits to Probabilistic Programs and Back. ICAART (1) (2021)
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 (2021)
Anji Liu, Guy Van den Broeck
Tractable Regularization of Probabilistic Circuits. CoRR (2021)
Honghua Zhang, Brendan Juba, Guy Van den Broeck
Probabilistic Generating Circuits. CoRR (2021)
Anji Liu, Guy Van den Broeck
Tractable Regularization of Probabilistic Circuits. NeurIPS (2021)
Kareem Ahmed, Eric Wang, Guy Van den Broeck, Kai-Wei Chang
Leveraging Unlabeled Data for Entity-Relation Extraction through Probabilistic Constraint Satisfaction. CoRR (2021)
Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations. NeurIPS (2020)
Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck
Handling Missing Data in Decision Trees: A Probabilistic Approach. CoRR (2020)
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)
Anji Liu, Yitao Liang, Ji Liu, Guy Van den Broeck, Jianshu Chen
On Effective Parallelization of Monte Carlo Tree Search. CoRR (2020)
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 (2020)
Honghua Zhang, Steven Holtzen, Guy Van den Broeck
On the Relationship Between Probabilistic Circuits and Determinantal Point Processes. CoRR (2020)
Steven Holtzen, Guy Van den Broeck, Todd D. Millstein
Scaling exact inference for discrete probabilistic programs. Proc. ACM Program. Lang. 4 (OOPSLA) (2020)
Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst
Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams. IDA (2020)
Anji Liu, Yitao Liang, Guy Van den Broeck
Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration. AAMAS (2020)
Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto
SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning. CoRL (2020)
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)
Honghua Zhang, Steven Holtzen, Guy Van den Broeck
On the Relationship Between Probabilistic Circuits and Determinantal Point Processes. UAI (2020)
Aishwarya Sivaraman, Golnoosh Farnadi, Todd D. Millstein, Guy Van den Broeck
Counterexample-Guided Learning of Monotonic Neural Networks. NeurIPS (2020)
Meihua Dang, Antonio Vergari, Guy Van den Broeck
Strudel: Learning Structured-Decomposable Probabilistic Circuits. CoRR (2020)
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 (2020)
YooJung Choi, Meihua Dang, Guy Van den Broeck
Group Fairness by Probabilistic Modeling with Latent Fair Decisions. CoRR (2020)
Aishwarya Sivaraman, Golnoosh Farnadi, Todd D. Millstein, Guy Van den Broeck
Counterexample-Guided Learning of Monotonic Neural Networks. CoRR (2020)
Tal Friedman, Guy Van den Broeck
Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings. CoRR (2020)
Kristian Kersting, Miryung Kim, Guy Van den Broeck, Thomas Zimmermann
SE4ML - Software Engineering for AI-ML-based Systems (Dagstuhl Seminar 20091). Dagstuhl Reports 10 (2) (2020)
Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu
On the Tractability of SHAP Explanations. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Guy Van den Broeck