| Chapter 1. Neural-Symbolic Learning and Reasoning: A Survey and Interpretation 1 TR Besold, A d’Avila Garcez, S Bader, H Bowman, P Domingos, P Hitzler, ... Neuro-Symbolic Artificial Intelligence: The State of the Art, 1-51, 2021 | 382 | 2021 |
| Discovery of fraud rules for telecommunications—challenges and solutions S Rosset, U Murad, E Neumann, Y Idan, G Pinkas Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999 | 202 | 1999 |
| Reasoning, nonmonotonicity and learning in connectionist networks that capture propositional knowledge G Pinkas Artificial Intelligence 77 (2), 203-247, 1995 | 171 | 1995 |
| Propositional non-monotonic reasoning and inconsistency in symmetric neural networks G Pinkas | 122 | 1991 |
| Symmetric neural networks and propositional logic satisfiability G Pinkas Neural Computation 3 (2), 282-291, 1991 | 104 | 1991 |
| Unsupervised profiling for identifying superimposed fraud U Murad, G Pinkas Principles of Data Mining and Knowledge Discovery: Third European Conference …, 1999 | 92 | 1999 |
| SARS-CoV-2 Detection From Voice G. Pinkas, Y. Karny, A. Malachi, G. Barkai, G. Bachar and V. Aharonson IEEE Open Journal of Engineering in Medicine and Biology 1, 268-274, 2020 | 85* | 2020 |
| Reasoning from inconsistency: A taxonomy of principles for resolving conflict G Pinkas, RP Loui Proceedings of the Third International Conference on Principles of Knowledge …, 1992 | 74 | 1992 |
| Telecommunications system for generating a three-level customer behavior profile and for detecting deviation from the profile to identify fraud U Murad, G Pinkas US Patent 7,035,823, 2006 | 66 | 2006 |
| Improving connectionist energy minimization G Pinkas, R Dechter Journal of Artificial Intelligence Research 3, 223-248, 1995 | 46 | 1995 |
| Energy minimization and the satisfiability of propositional calculus G Pinkas Neural Computation 3 (2), 282-291, 1991 | 39 | 1991 |
| Constructing proofs in symmetric networks G Pinkus Advances in neural information processing systems 4, 1991 | 28 | 1991 |
| Neural-symbolic learning and reasoning: A survey and interpretation, CoRR abs/1711.03902 (2017) TR Besold, ASA Garcez, S Bader, H Bowman, PM Domingos, P Hitzler, ... arXiv preprint arXiv:1711.03902, 2017 | 20 | 2017 |
| Logical inference in symmetric connectionist networks G Pinkas Washington University in St. Louis, 1992 | 20 | 1992 |
| Telecommunications system for generating a three-level customer behavior profile and for detecting deviation from the profile to identify fraud U Murad, G Pinkas US Patent 6,526,389, 2003 | 19 | 2003 |
| Representing, binding, retrieving and unifying relational knowledge using pools of neural binders G Pinkas, P Lima, S Cohen Biologically Inspired Cognitive Architectures 6, 87-95, 2013 | 18 | 2013 |
| Propositional logic, nonmonotonic reasoning and symmetric networks—On bridging the gap between symbolic and connectionist knowledge representation G Pinkas Neural networks for knowledge representation and inference, 175-204, 2013 | 12 | 2013 |
| Energy minimization and the satisfiability of propositional logic G Pinkas Connectionist Models, 23-31, 1991 | 11 | 1991 |
| A dynamic binding mechanism for retrieving and unifying complex predicate-logic knowledge G Pinkas, P Lima, S Cohen Artificial Neural Networks and Machine Learning–ICANN 2012: 22nd …, 2012 | 10 | 2012 |
| Logical inference in symmetric neural networks G Pinkas D. Sc. Thesis, Sever Institute of Technology, Washington University, Saint …, 1992 | 9 | 1992 |
