| 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 | 455 | 2021 |
| Neural-symbolic learning systems AS d’Avila Garcez, LC Lamb, DM Gabbay Neural-Symbolic Cognitive Reasoning, 35-54, 2009 | 421 | 2009 |
| Neurosymbolic AI: the 3rd wave AA Garcez, LC Lamb Artificial Intelligence Review 56 (11), 12387-12406, 2023 | 407 | 2023 |
| Neural-symbolic computing: An effective methodology for principled integration of machine learning and reasoning AA Garcez, M Gori, LC Lamb, L Serafini, M Spranger, SN Tran arXiv preprint arXiv:1905.06088, 2019 | 360 | 2019 |
| Logic tensor networks S Badreddine, AA Garcez, L Serafini, M Spranger Artificial Intelligence 303, 103649, 2022 | 321 | 2022 |
| Neural-symbolic cognitive reasoning AS D'Avila Garcez, LC Lamb, DM Gabbay Neural-Symbolic Cognitive Reasoning:, Cognitive Technologies, Volume. ISBN …, 2009 | 304* | 2009 |
| Logic tensor networks: Deep learning and logical reasoning from data and knowledge L Serafini, AA Garcez arXiv preprint arXiv:1606.04422, 2016 | 301 | 2016 |
| Symbolic knowledge extraction from trained neural networks: A sound approach AS d'Avila Garcez, K Broda, DM Gabbay Artificial Intelligence 125 (1-2), 155-207, 2001 | 287 | 2001 |
| Logic tensor networks for semantic image interpretation I Donadello, L Serafini, AA Garcez arXiv preprint arXiv:1705.08968, 2017 | 286 | 2017 |
| The Connectionist Inductive Learning and Logic Programming System AG AS, G Zaverucha Applied Intelligence 11 (1), 59-77, 1999 | 257 | 1999 |
| Neural-Symbolic Learning and Reasoning: Contributions and Challenges. ASA Garcez, TR Besold, L De Raedt, P Földiak, P Hitzler, T Icard, ... AAAI Spring Symposia, 18-21, 2015 | 226 | 2015 |
| Graph neural networks meet neural-symbolic computing: A survey and perspective LC Lamb, A Garcez, M Gori, M Prates, P Avelar, M Vardi arXiv preprint arXiv:2003.00330, 2020 | 219 | 2020 |
| Fast relational learning using bottom clause propositionalization with artificial neural networks MVM França, G Zaverucha, AS d’Avila Garcez Machine learning 94, 81-104, 2014 | 179 | 2014 |
| Deep logic networks: Inserting and extracting knowledge from deep belief networks SN Tran, ASA Garcez IEEE transactions on neural networks and learning systems 29 (2), 246-258, 2016 | 167 | 2016 |
| Measurable counterfactual local explanations for any classifier A White, A d’Avila Garcez ECAI 2020, 2529-2535, 2020 | 131 | 2020 |
| Learning and reasoning with logic tensor networks L Serafini, AS d’Avila Garcez Conference of the italian association for artificial intelligence, 334-348, 2016 | 122 | 2016 |
| Speaker recognition with hybrid features from a deep belief network H Ali, SN Tran, E Benetos, AS d’Avila Garcez Neural Computing and Applications 29, 13-19, 2018 | 105 | 2018 |
| Predicting online gambling self-exclusion: An analysis of the performance of supervised machine learning models C Percy, M França, S Dragičević, A d’Avila Garcez International Gambling Studies 16 (2), 193-210, 2016 | 85 | 2016 |
| A neural-symbolic cognitive agent for online learning and reasoning HLHL de Penning, ASA Garcez, LC Lamb, JJC Meyer Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), 2011 | 73 | 2011 |
| Value-based argumentation frameworks as neural-symbolic learning systems AS D'Avila Garcez, DM Gabbay, LC Lamb Journal of Logic and Computation 15 (6), 1041-1058, 2005 | 66 | 2005 |
Luis LambComputer Science, AI, Innovation在 mit.edu 的电子邮件经过验证
