Ahmed, Kareem

15 publications

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
NeurIPSW 2024 Controllable Generation via Locally Constrained Resampling Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck
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
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
AISTATS 2023 Semantic Strengthening of Neuro-Symbolic Learning Kareem Ahmed, Kai-Wei Chang, Guy Broeck
UAI 2022 Neuro-Symbolic Entropy Regularization Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Broeck
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