Cooperative Heterogeneous Multi-Robot Systems: A Survey Y Rizk, M Awad, E Tunstel ACM Computing Surveys 52 (2), 29:1-29:31, 2019 | 427 | 2019 |
Decision Making in Multi-Agent Systems: A Survey Y Rizk, M Awad, EW Tunstel IEEE Transactions on Cognitive and Developmental Systems 10 (3), 514--529, 2018 | 249 | 2018 |
From Robotic Process Automation to Intelligent Process Automation T Chakraborti, V Isahagian, R Khalaf, Y Khazaeni, V Muthusamy, Y Rizk, ... Business Process Management: Blockchain and Robotic Process Automation Forum …, 2020 | 189 | 2020 |
Damage Identification in Social Media Posts using Multimodal Deep Learning H Mouzannar, Y Rizk, M Awad The 15th International Conference on Information Systems for Crisis Response …, 2018 | 150 | 2018 |
The biggest business process management problems to solve before we die I Beerepoot, C Di Ciccio, HA Reijers, S Rinderle-Ma, W Bandara, ... Computers in Industry 146, 103837, 2023 | 134 | 2023 |
Deep belief networks and cortical algorithms: A comparative study for supervised classification Y Rizk, N Hajj, N Mitri, M Awad Applied Computing and Informatics, 2018 | 77 | 2018 |
A conversational digital assistant for intelligent process automation Y Rizk, V Isahagian, S Boag, Y Khazaeni, M Unuvar, V Muthusamy, ... Business Process Management: Blockchain and Robotic Process Automation Forum …, 2020 | 49 | 2020 |
A deep transfer learning framework for seismic data analysis: A case study on bright spot detection J El Zini, Y Rizk, M Awad IEEE Transactions on Geoscience and Remote Sensing 58 (5), 3202-3212, 2019 | 44 | 2019 |
A unified conversational assistant framework for business process automation Y Rizk, A Bhandwalder, S Boag, T Chakraborti, V Isahagian, Y Khazaeni, ... arXiv preprint arXiv:2001.03543, 2020 | 38 | 2020 |
A Computationally Efficient Multi-modal Classification Approach of Disaster-related Twitter Images Y Rizk, HS Jomaa, M Awad, C Castillo ACM SAC, 2050-2059, 2019 | 36 | 2019 |
On Extreme Learning Machines in Sequential and Time Series Prediction: A Non-Iterative and Approximate Training Algorithm for Recurrent Neural Networks Y Rizk, M Awad Neurocomputing, 2018 | 27 | 2018 |
A Subjectivity Classification Framework for Sports Articles using Improved Cortical Algorithms N Hajj, Y Rizk, M Awad Neural Computing & Applications, 1-17, 2018 | 27 | 2018 |
Towards a deep learning question-answering specialized chatbot for objective structured clinical examinations J El Zini, Y Rizk, M Awad, J Antoun 2019 International Joint Conference on Neural Networks (IJCNN), 1-9, 2019 | 23 | 2019 |
An Optimized Parallel Implementation of Non-Iteratively Trained Recurrent Neural Networks J El Zini, Y Rizk, M Awad Journal of Artificial Intelligence and Soft Computing Research 11 (1), 33-50, 2021 | 20 | 2021 |
From natural language to workflows: Towards emergent intelligence in robotic process automation T Chakraborti, Y Rizk, V Isahagian, B Aksar, F Fuggitti International Conference on Business Process Management, 123-137, 2022 | 16 | 2022 |
Explainable composition of aggregated assistants S Sreedharan, T Chakraborti, Y Rizk, Y Khazaeni arXiv preprint arXiv:2011.10707, 2020 | 14 | 2020 |
Towards large language model-based personal agents in the enterprise: Current trends and open problems V Muthusamy, Y Rizk, K Kate, P Venkateswaran, V Isahagian, A Gulati, ... Findings of the Association for Computational Linguistics: EMNLP 2023, 6909-6921, 2023 | 13 | 2023 |
A mapreduce cortical algorithms implementation for unsupervised learning of big data N Hajj, Y Rizk, M Awad Procedia Computer Science 53, 327-334, 2015 | 13 | 2015 |
A local mixture based SVM for an efficient supervised binary classification Y Rizk, N Mitri, M Awad The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013 | 13 | 2013 |
Granite-function calling model: Introducing function calling abilities via multi-task learning of granular tasks I Abdelaziz, K Basu, M Agarwal, S Kumaravel, M Stallone, R Panda, ... arXiv preprint arXiv:2407.00121, 2024 | 12 | 2024 |