Van Den Broeck, Guy

100 publications

NeurIPS 2025 Accelerating Diffusion LLMs via Adaptive Parallel Decoding Daniel Mingyi Israel, Guy Van den Broeck, Aditya Grover

ICLR 2025 Controllable Generation via Locally Constrained Resampling Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck

ICLRW 2025 Controllable Generation via Locally Constrained Resampling Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck

ICLR 2025 Discrete Copula Diffusion Anji Liu, Oliver Broadrick, Mathias Niepert, Guy Van den Broeck

ICLR 2025 Learning to Discretize Denoising Diffusion ODEs Vinh Tong, Dung Trung Hoang, Anji Liu, Guy Van den Broeck, Mathias Niepert

TMLR 2025 On the Challenges and Opportunities in Generative AI Laura Manduchi, Clara Meister, 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 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

AAAI 2025 On the Relationship Between Monotone and Squared Probabilistic Circuits Benjie Wang, Guy Van den Broeck

NeurIPS 2025 Plug-and-Play Context Feature Reuse for Efficient Masked Generation Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang

NeurIPS 2025 Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion Vinh Tong, Dung Trung Hoang, Anji Liu, Guy Van den Broeck, Mathias Niepert

ICML 2025 Scaling Probabilistic Circuits via Monarch Matrices Honghua Zhang, Meihua Dang, Benjie Wang, Stefano Ermon, Nanyun Peng, Guy Van Den Broeck

ICLRW 2025 Symmetry-Preserving Diffusion Models via Target Symmetrization Vinh Tong, Yun Ye, Dung Trung Hoang, Anji Liu, Guy Van den Broeck, Mathias Niepert

ICML 2025 TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation Gwen Yidou Weng, Benjie Wang, Guy Van Den Broeck

ICML 2025 The Limits of Tractable Marginalization Oliver Broadrick, Sanyam Agarwal, Guy Van Den Broeck, Markus Bläser

ICML 2025 Tractable Transformers for Flexible Conditional Generation Anji Liu, Xuejie Liu, Dayuan Zhao, Mathias Niepert, Yitao Liang, Guy Van Den Broeck

NeurIPS 2024 A Compositional Atlas for Algebraic Circuits Benjie Wang, Denis Deratani Mauá, Guy Van den Broeck, YooJung Choi

NeurIPS 2024 A Tractable Inference Perspective of Offline RL Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang

ICMLW 2024 A Tractable Inference Perspective of Offline RL Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang

NeurIPS 2024 Adaptable Logical Control for Large Language Models Honghua Zhang, Po-Nien Kung, Masahiro Yoshida, Guy Van den Broeck, Nanyun Peng

NeurIPSW 2024 Controllable Generation via Locally Constrained Resampling Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck

ICMLW 2024 Fast and Memory-Efficient Multi-Sequence Generation via Structured Masking Daniel Mingyi Israel, Siyan Zhao, Guy Van den Broeck, Aditya Grover

ICLR 2024 Image Inpainting via Tractable Steering of Diffusion Models Anji Liu, Mathias Niepert, Guy Van den Broeck

ICMLW 2024 Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models Siyan Zhao, Daniel Mingyi Israel, Guy Van den Broeck, Aditya Grover

ICLR 2024 Probabilistically Rewired Message-Passing Neural Networks Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris

ICML 2024 Scaling Tractable Probabilistic Circuits: A Systems Perspective Anji Liu, Kareem Ahmed, Guy Van Den Broeck

NeurIPS 2023 A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck

NeurIPS 2023 A Unified Approach to Count-Based Weakly Supervised Learning Vinay Shukla, Zhe Zeng, Kareem Ahmed, Guy Van den Broeck

ICMLW 2023 A Unified Approach to Count-Based Weakly-Supervised Learning Vinay Shukla, Zhe Zeng, Kareem Ahmed, Guy Van den Broeck

AAAI 2023 Certifying Fairness of Probabilistic Circuits Nikil Roashan Selvam, Guy Van den Broeck, YooJung Choi

NeurIPS 2023 Collapsed Inference for Bayesian Deep Learning Zhe Zeng, Guy Van den Broeck

ICMLW 2023 Collapsed Inference for Bayesian Deep Learning Zhe Zeng, Guy Van den Broeck

NeurIPSW 2023 Gradient Estimation for Exactly-$k$ Constraints Ruoyan Li, Dipti Ranjan Sahu, Guy Van den Broeck, Zhe Zeng

IJCAI 2023 On the Paradox of Learning to Reason from Data Honghua Zhang, Liunian Harold Li, Tao Meng, Kai-Wei Chang, Guy Van den Broeck

AAAI 2023 Out-of-Distribution Generalization by Neural-Symbolic Joint Training Anji Liu, Hongming Xu, Guy Van den Broeck, Yitao Liang

ICMLW 2023 Probabilistic Task-Adaptive Graph Rewiring Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck, Mathias Niepert, Christopher Morris

ICMLW 2023 SIMPLE: A Gradient Estimator for $k$-Subset Sampling Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck

ICLR 2023 SIMPLE: A Gradient Estimator for K-Subset Sampling Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck

UAI 2023 Scaling Integer Arithmetic in Probabilistic Programs William X. Cao, Poorva Garg, Ryan Tjoa, Steven Holtzen, Todd Millstein, Guy Van den Broeck

ICLR 2023 Scaling up Probabilistic Circuits by Latent Variable Distillation Anji Liu, Honghua Zhang, Guy Van den Broeck

ICML 2023 Tractable Control for Autoregressive Language Generation Honghua Zhang, Meihua Dang, Nanyun Peng, Guy Van Den Broeck

ICML 2023 Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits Xuejie Liu, Anji Liu, Guy Van Den Broeck, Yitao Liang

AISTATS 2022 Solving Marginal MAP Exactly by Probabilistic Circuit Transformations Yoojung Choi, Tal Friedman, Guy Van Den Broeck

ICLR 2022 Lossless Compression with Probabilistic Circuits Anji Liu, Stephan Mandt, Guy Van den Broeck

JAIR 2022 On the Tractability of SHAP Explanations Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu

AAAI 2022 PYLON: A PyTorch Framework for Learning with Constraints Kareem Ahmed, Tao Li, Thy Ton, Quan Guo, Kai-Wei Chang, Parisa Kordjamshidi, Vivek Srikumar, Guy Van den Broeck, Sameer Singh

NeurIPS 2022 Semantic Probabilistic Layers for Neuro-Symbolic Learning Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari

NeurIPS 2022 Sparse Probabilistic Circuits via Pruning and Growing Meihua Dang, Anji Liu, Guy Van den Broeck

NeurIPS 2021 A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck

AAAI 2021 Group Fairness by Probabilistic Modeling with Latent Fair Decisions YooJung Choi, Meihua Dang, Guy Van den Broeck

AAAI 2021 Juice: A Julia Package for Logic and Probabilistic Circuits Meihua Dang, Pasha Khosravi, Yitao Liang, Antonio Vergari, Guy Van den Broeck

AAAI 2021 On the Tractability of SHAP Explanations Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu

ICML 2021 Probabilistic Generating Circuits Honghua Zhang, Brendan Juba, Guy Van Den Broeck

IJCAI 2021 Probabilistic Sufficient Explanations Eric Wang, Pasha Khosravi, Guy Van den Broeck

NeurIPS 2021 Tractable Regularization of Probabilistic Circuits Anji Liu, Guy Van den Broeck

NeurIPS 2020 Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman, Golnoosh Farnadi, Todd Millstein, Guy Van den Broeck

ICML 2020 Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van Den Broeck, Kristian Kersting, Zoubin Ghahramani

ICMLW 2020 Handling Missing Data in Decision Trees: A Probabilistic Approach Pasha Khosravi, Antonio Vergari, YooJung Choi, Yitao Liang, Guy Van den Broeck

AAAI 2020 Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns YooJung Choi, Golnoosh Farnadi, Behrouz Babaki, Guy Van den Broeck

NeurIPS 2020 Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck

CoRL 2020 SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto

ICML 2020 Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van Den Broeck

UAI 2019 Generating and Sampling Orbits for Lifted Probabilistic Inference Steven Holtzen, Todd Millstein, Guy Van den Broeck

AAAI 2019 Learning Logistic Circuits Yitao Liang, Guy Van den Broeck

IJCAI 2019 On Constrained Open-World Probabilistic Databases Tal Friedman, Guy Van den Broeck

NeurIPS 2019 On Tractable Computation of Expected Predictions Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck

NeurIPS 2019 Smoothing Structured Decomposable Circuits Andy Shih, Guy Van den Broeck, Paul Beame, Antoine Amarilli

NeurIPS 2019 Towards Hardware-Aware Tractable Learning of Probabilistic Models Laura I Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck

IJCAI 2019 What to Expect of Classifiers? Reasoning About Logistic Regression with Missing Features Pasha Khosravi, Yitao Liang, YooJung Choi, Guy Van den Broeck

NeurIPS 2018 Approximate Knowledge Compilation by Online Collapsed Importance Sampling Tal Friedman, Guy Van den Broeck

IJCAI 2018 On Robust Trimming of Bayesian Network Classifiers YooJung Choi, Guy Van den Broeck

UAI 2017 Learning the Structure of Probabilistic Sentential Decision Diagrams Yitao Liang, Jessa Bekker, Guy Van den Broeck

IJCAI 2017 Open-World Probabilistic Databases: An Abridged Report Ismail Ilkan Ceylan, Adnan Darwiche, Guy Van den Broeck

IJCAI 2017 Optimal Feature Selection for Decision Robustness in Bayesian Networks YooJung Choi, Adnan Darwiche, Guy Van den Broeck

UAI 2017 Probabilistic Program Abstractions Steven Holtzen, Todd D. Millstein, Guy Van den Broeck

AAAI 2016 Component Caching in Hybrid Domains with Piecewise Polynomial Densities Vaishak Belle, Guy Van den Broeck, Andrea Passerini

IJCAI 2016 First-Order Model Counting in a Nutshell Guy Van den Broeck

IJCAI 2016 Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report Vaishak Belle, Guy Van den Broeck, Andrea Passerini

MLJ 2016 Lifted Generative Learning of Markov Logic Networks Jan Van Haaren, Guy Van den Broeck, Wannes Meert, Jesse Davis

NeurIPS 2016 New Liftable Classes for First-Order Probabilistic Inference Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole

IJCAI 2015 Anytime Inference in Probabilistic Logic Programs with Tp-Compilation Jonas Vlasselaer, Guy Van den Broeck, Angelika Kimmig, Wannes Meert, Luc De Raedt

UAI 2015 Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data Guy Van den Broeck, Karthika Mohan, Arthur Choi, Adnan Darwiche, Judea Pearl

UAI 2015 Hashing-Based Approximate Probabilistic Inference in Hybrid Domains Vaishak Belle, Guy Van den Broeck, Andrea Passerini

IJCAI 2015 Inducing Probabilistic Relational Rules from Probabilistic Examples Luc De Raedt, Anton Dries, Ingo Thon, Guy Van den Broeck, Mathias Verbeke

AAAI 2015 Lifted Probabilistic Inference for Asymmetric Graphical Models Guy Van den Broeck, Mathias Niepert

AAAI 2015 On the Role of Canonicity in Knowledge Compilation Guy Van den Broeck, Adnan Darwiche

ECML-PKDD 2015 ProbLog2: Probabilistic Logic Programming Anton Dries, Angelika Kimmig, Wannes Meert, Joris Renkens, Guy Van den Broeck, Jonas Vlasselaer, Luc De Raedt

IJCAI 2015 Probabilistic Inference in Hybrid Domains by Weighted Model Integration Vaishak Belle, Andrea Passerini, Guy Van den Broeck

NeurIPS 2015 Tractable Learning for Complex Probability Queries Jessa Bekker, Jesse Davis, Arthur Choi, Adnan Darwiche, Guy Van den Broeck

IJCAI 2015 Tractable Learning for Structured Probability Spaces: A Case Study in Learning Preference Distributions Arthur Choi, Guy Van den Broeck, Adnan Darwiche

AAAI 2014 Explanation-Based Approximate Weighted Model Counting for Probabilistic Logics Joris Renkens, Angelika Kimmig, Guy Van den Broeck, Luc De Raedt

AAAI 2014 Tractability Through Exchangeability: A New Perspective on Efficient Probabilistic Inference Mathias Niepert, Guy Van den Broeck

UAI 2014 Understanding the Complexity of Lifted Inference and Asymmetric Weighted Model Counting Eric Gribkoff, Guy Van den Broeck, Dan Suciu

AISTATS 2013 Completeness Results for Lifted Variable Elimination Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel

NeurIPS 2013 On the Complexity and Approximation of Binary Evidence in Lifted Inference Guy Van den Broeck, Adnan Darwiche

AAAI 2012 Conditioning in First-Order Knowledge Compilation and Lifted Probabilistic Inference Guy Van den Broeck, Jesse Davis

MLJ 2012 K-Optimal: A Novel Approximate Inference Algorithm for ProbLog Joris Renkens, Guy Van den Broeck, Siegfried Nijssen

UAI 2012 Lifted Relax, Compensate and Then Recover: From Approximate to Exact Lifted Probabilistic Inference Guy Van den Broeck, Arthur Choi, Adnan Darwiche

AAAI 2011 An Algebraic Prolog for Reasoning About Possible Worlds Angelika Kimmig, Guy Van den Broeck, Luc De Raedt

UAI 2011 Inference in Probabilistic Logic Programs Using Weighted CNF's Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt

IJCAI 2011 Lifted Probabilistic Inference by First-Order Knowledge Compilation Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt

AAAI 2010 DTProbLog: A Decision-Theoretic Probabilistic Prolog Guy Van den Broeck, Ingo Thon, Martijn van Otterlo, Luc De Raedt