Novel Single Image deblurring Technique using Sparse representation and Discrete Radon Transform. - Ibrahim M. El-Henawy; A. A. Ali; Kareem Ahmed; Hadeer Adel (ICCTA, 2015)

Content-Based Image Retrieval Using Multiresolution Analysis Of Shape-Based Classified Images. - Ibrahim M. El-Henawy; Kareem Ahmed (CoRR, 2016)

Action recognition using fast HOG3D of integral videos and Smith-Waterman partial matching. - Ibrahim M. El-Henawy; Kareem Ahmed; Hamdi Mahmoud (IET Image Process., 2018)

Leveraging Unlabeled Data for Entity-Relation Extraction through Probabilistic Constraint Satisfaction. - Kareem Ahmed; Eric Wang; Guy Van den Broeck; Kai-Wei Chang (CoRR, 2021)

PYLON: A PyTorch Framework for Learning with Constraints. - Kareem Ahmed; Tao Li 039; Thy Ton; Quan Guo; Kai-Wei Chang; Parisa Kordjamshidi; Vivek Srikumar; Guy Van den Broeck; Sameer Singh 001 (AAAI, 2022)

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

Neuro-symbolic entropy regularization. - Kareem Ahmed; Eric Wang; Kai-Wei Chang; Guy Van den Broeck (UAI, 2022)

Performance Evaluation of Infrared Image Enhancement Techniques. - Rania Gaber; AbdElmgied Ali; Kareem Ahmed (CoRR, 2022)

A New Chaotic-Based RGB Image Encryption Technique Using a Nonlinear Rotational 16 × 16 DNA Playfair Matrix. - Dina Ibrahim; Kareem Ahmed; Mohamed Abdallah; Abdelmgeid A. Ali (Cryptogr., 2022)

Performance evaluation of salient object detection techniques. - Kareem Ahmed; Mai A. Gad; Amal Elsayed Aboutabl (Multim. Tools Appl., 2022)

Semantic Strengthening of Neuro-Symbolic Learning. - Kareem Ahmed; Kai-Wei Chang; Guy Van den Broeck (AISTATS, 2023)

SIMPLE: A Gradient Estimator for k-Subset Sampling. - Kareem Ahmed; Zhe Zeng; Mathias Niepert; Guy Van den Broeck (ICLR, 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 (NeurIPS, 2023)

Semantic Loss Functions for Neuro-Symbolic Structured Prediction. - 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 (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Where is the signal in tokenization space? - Renato Lui Geh; Honghua Zhang; Kareem Ahmed; Benjie Wang 001; Guy Van den Broeck (EMNLP, 2024)

Probabilistically Rewired Message-Passing Neural Networks. - Chendi Qian; Andrei Manolache; Kareem Ahmed; Zhe Zeng; Guy Van den Broeck; Mathias Niepert; Christopher Morris 001 (ICLR, 2024)

Scaling Tractable Probabilistic Circuits: A Systems Perspective. - Anji Liu; Kareem Ahmed; Guy Van den Broeck (ICML, 2024)

Semantic Loss Functions for Neuro-Symbolic Structured Prediction. - 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 (CoRR, 2024)

Snake species classification using deep learning techniques. - Kareem Ahmed; Mai A. Gad; Amal Elsayed Aboutabl (Multim. Tools Appl., 2024)

Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods. - Asmaa Ameen; Ibrahim Eldesouky Fattoh; Tarek Abd El-Hafeez; Kareem Ahmed (J. Big Data, 2024)

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

Semantic Probabilistic Control of Language Models. - Kareem Ahmed; Catarina G. Belém; Padhraic Smyth; Sameer Singh 001 (CoRR, 2025)