Artigos de revistas sobre o tema "Neuro-Symbolic Artificial intelligence"
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Marra, Giuseppe. "From Statistical Relational to Neuro-Symbolic Artificial Intelligence". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 20 (24 de março de 2024): 22678. http://dx.doi.org/10.1609/aaai.v38i20.30294.
Texto completo da fonteMorel, Gilles. "Neuro-symbolic A.I. for the smart city". Journal of Physics: Conference Series 2042, n.º 1 (1 de novembro de 2021): 012018. http://dx.doi.org/10.1088/1742-6596/2042/1/012018.
Texto completo da fontevan Bekkum, Michael, Maaike de Boer, Frank van Harmelen, André Meyer-Vitali e Annette ten Teije. "Modular design patterns for hybrid learning and reasoning systems". Applied Intelligence 51, n.º 9 (18 de junho de 2021): 6528–46. http://dx.doi.org/10.1007/s10489-021-02394-3.
Texto completo da fonteEbrahimi, Monireh, Aaron Eberhart, Federico Bianchi e Pascal Hitzler. "Towards bridging the neuro-symbolic gap: deep deductive reasoners". Applied Intelligence 51, n.º 9 (6 de fevereiro de 2021): 6326–48. http://dx.doi.org/10.1007/s10489-020-02165-6.
Texto completo da fonteBarbosa, Raul, Douglas O. Cardoso, Diego Carvalho e Felipe M. G. França. "Weightless neuro-symbolic GPS trajectory classification". Neurocomputing 298 (julho de 2018): 100–108. http://dx.doi.org/10.1016/j.neucom.2017.11.075.
Texto completo da fonteBahamid, Alala, Azhar Mohd Ibrahim e Amir Akramin Shafie. "Crowd evacuation with human-level intelligence via neuro-symbolic approach". Advanced Engineering Informatics 60 (abril de 2024): 102356. http://dx.doi.org/10.1016/j.aei.2024.102356.
Texto completo da fonteŠkrlj, Blaž, Matej Martinc, Nada Lavrač e Senja Pollak. "autoBOT: evolving neuro-symbolic representations for explainable low resource text classification". Machine Learning 110, n.º 5 (14 de abril de 2021): 989–1028. http://dx.doi.org/10.1007/s10994-021-05968-x.
Texto completo da fontePrentzas, Jim, e Ioannis Hatzilygeroudis. "Neurules and connectionist expert systems: Unexplored neuro-symbolic reasoning aspects". Intelligent Decision Technologies 15, n.º 4 (10 de janeiro de 2022): 761–77. http://dx.doi.org/10.3233/idt-210211.
Texto completo da fonteShilov, Nikolay, Andrew Ponomarev e Alexander Smirnov. "The Analysis of Ontology-Based Neuro-Symbolic Intelligence Methods for Collaborative Decision Support". Informatics and Automation 22, n.º 3 (22 de maio de 2023): 576–615. http://dx.doi.org/10.15622/ia.22.3.4.
Texto completo da fonteKishor, Rabinandan. "Neuro-Symbolic AI: Bringing a new era of Machine Learning". International Journal of Research Publication and Reviews 03, n.º 12 (2022): 2326–36. http://dx.doi.org/10.55248/gengpi.2022.31271.
Texto completo da fonteSmirnov, A. V., A. V. Ponomarev, N. G. Shilov e T. V. Levashova. "Collaborative Decision Support Systems Based on Neuro-Symbolic Artificial Intelligence: Problems and Generalized Conceptual Model". Scientific and Technical Information Processing 50, n.º 6 (dezembro de 2023): 635–45. http://dx.doi.org/10.3103/s0147688223060151.
Texto completo da fonteSkryagin, Arseny, Daniel Ochs, Devendra Singh Dhami e Kristian Kersting. "Scalable Neural-Probabilistic Answer Set Programming". Journal of Artificial Intelligence Research 78 (16 de novembro de 2023): 579–617. http://dx.doi.org/10.1613/jair.1.15027.
Texto completo da fonteSouici-Meslati, Labiba, e Mokhtar Sellami. "A Hybrid Neuro-Symbolic Approach for Arabic Handwritten Word Recognition". Journal of Advanced Computational Intelligence and Intelligent Informatics 10, n.º 1 (20 de janeiro de 2006): 17–25. http://dx.doi.org/10.20965/jaciii.2006.p0017.
Texto completo da fonteOnchis, Darian, Codruta Istin e Eduard Hogea. "A Neuro-Symbolic Classifier with Optimized Satisfiability for Monitoring Security Alerts in Network Traffic". Applied Sciences 12, n.º 22 (12 de novembro de 2022): 11502. http://dx.doi.org/10.3390/app122211502.
Texto completo da fontePapadimitriou, Stergios, e Constantinos Terzidis. "Symbolic adaptive neuro-fuzzy inference for data mining of heterogenous data". Intelligent Data Analysis 7, n.º 4 (27 de agosto de 2003): 327–46. http://dx.doi.org/10.3233/ida-2003-7405.
Texto completo da fonteFeng, Yufei, Xiaoyu Yang, Xiaodan Zhu e Michael Greenspan. "Neuro-symbolic Natural Logic with Introspective Revision for Natural Language Inference". Transactions of the Association for Computational Linguistics 10 (2022): 240–56. http://dx.doi.org/10.1162/tacl_a_00458.
Texto completo da fonteYuan, Ye, Bo Tang, Tianfei Zhou, Zhiwei Zhang e Jianbin Qin. "nsDB: Architecting the Next Generation Database by Integrating Neural and Symbolic Systems". Proceedings of the VLDB Endowment 17, n.º 11 (julho de 2024): 3283–89. http://dx.doi.org/10.14778/3681954.3682000.
Texto completo da fontePallagani, Vishal, Bharath Chandra Muppasani, Kaushik Roy, Francesco Fabiano, Andrea Loreggia, Keerthiram Murugesan, Biplav Srivastava, Francesca Rossi, Lior Horesh e Amit Sheth. "On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)". Proceedings of the International Conference on Automated Planning and Scheduling 34 (30 de maio de 2024): 432–44. http://dx.doi.org/10.1609/icaps.v34i1.31503.
Texto completo da fontePalconit, Maria Gemel B., Ronnie S. Concepcion II, Jonnel D. Alejandrino, Michael E. Pareja, Vincent Jan D. Almero, Argel A. Bandala, Ryan Rhay P. Vicerra, Edwin Sybingco, Elmer P. Dadios e Raouf N. G. Naguib. "Three-Dimensional Stereo Vision Tracking of Multiple Free-Swimming Fish for Low Frame Rate Video". Journal of Advanced Computational Intelligence and Intelligent Informatics 25, n.º 5 (20 de setembro de 2021): 639–46. http://dx.doi.org/10.20965/jaciii.2021.p0639.
Texto completo da fonteHua, Hua, Dongxu Li, Ruiqi Li, Peng Zhang, Jochen Renz e Anthony Cohn. "Towards Explainable Action Recognition by Salient Qualitative Spatial Object Relation Chains". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 5 (28 de junho de 2022): 5710–18. http://dx.doi.org/10.1609/aaai.v36i5.20513.
Texto completo da fontePrentzas, Jim, e Ioannis Hatzilygeroudis. "Assessment of life insurance applications: an approach integrating neuro-symbolic rule-based with case-based reasoning". Expert Systems 33, n.º 2 (16 de novembro de 2015): 145–60. http://dx.doi.org/10.1111/exsy.12137.
Texto completo da fonteHu, Yiwen, e Markus J. Buehler. "Deep language models for interpretative and predictive materials science". APL Machine Learning 1, n.º 1 (1 de março de 2023): 010901. http://dx.doi.org/10.1063/5.0134317.
Texto completo da fonteSarker, Md Kamruzzaman, Lu Zhou, Aaron Eberhart e Pascal Hitzler. "Neuro-symbolic artificial intelligence". AI Communications, 16 de setembro de 2021, 1–13. http://dx.doi.org/10.3233/aic-210084.
Texto completo da fonteHitzler, Pascal, Aaron Eberhart, Monireh Ebrahimi, Md Kamruzzaman Sarker e Lu Zhou. "Neuro-Symbolic Approaches in Artificial Intelligence". National Science Review, 4 de março de 2022. http://dx.doi.org/10.1093/nsr/nwac035.
Texto completo da fonteBhuyan, Bikram Pratim, Amar Ramdane-Cherif, Ravi Tomar e T. P. Singh. "Neuro-symbolic artificial intelligence: a survey". Neural Computing and Applications, 6 de junho de 2024. http://dx.doi.org/10.1007/s00521-024-09960-z.
Texto completo da fonteLu, Zhen, Imran Afridi, Hong Jin Kang, Ivan Ruchkin e Xi Zheng. "Surveying neuro-symbolic approaches for reliable artificial intelligence of things". Journal of Reliable Intelligent Environments, 26 de julho de 2024. http://dx.doi.org/10.1007/s40860-024-00231-1.
Texto completo da fonteBueff, Andreas, e Vaishak Belle. "Learning explanatory logical rules in non-linear domains: a neuro-symbolic approach". Machine Learning, 8 de abril de 2024. http://dx.doi.org/10.1007/s10994-024-06538-7.
Texto completo da fonteShi, Tuo, Hui Zhang, Shiyu Cui, Jinchang Liu, Zixi Gu, Zhanfeng Wang, Xiaobing Yan e Qi Liu. "Stochastic neuro-fuzzy system implemented in memristor crossbar arrays". Science Advances 10, n.º 12 (22 de março de 2024). http://dx.doi.org/10.1126/sciadv.adl3135.
Texto completo da fonteHuang, Zhen. "Introducing Neuro-Symbolic Artificial Intelligence to Humanities and Social Sciences: Why Is It Possible and What Can Be Done?" TEM Journal, 25 de novembro de 2022, 1863–70. http://dx.doi.org/10.18421/tem114-54.
Texto completo da fonteHe, Hao-Yuan, Wang-Zhou Dai e Ming Li. "Reduced implication-bias logic loss for neuro-symbolic learning". Machine Learning, 30 de janeiro de 2024. http://dx.doi.org/10.1007/s10994-023-06436-4.
Texto completo da fonteMitchener, Ludovico, David Tuckey, Matthew Crosby e Alessandra Russo. "Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework". Machine Learning, 7 de abril de 2022. http://dx.doi.org/10.1007/s10994-022-06142-7.
Texto completo da fonteMunir, Md Shirajum, Ki Tae Kim, Apurba Adhikary, Walid Saad, Sachin Shetty, Seong-Bae Park e Choong Seon Hong. "Neuro-Symbolic Explainable Artificial Intelligence Twin for Zero-Touch IoE in Wireless Network". IEEE Internet of Things Journal, 2023, 1. http://dx.doi.org/10.1109/jiot.2023.3303713.
Texto completo da fonteDerkinderen, Vincent, Robin Manhaeve, Pedro Zuidberg Dos Martires e Luc De Raedt. "Semirings for probabilistic and neuro-symbolic logic programming". International Journal of Approximate Reasoning, janeiro de 2024, 109130. http://dx.doi.org/10.1016/j.ijar.2024.109130.
Texto completo da fonteBARBARA, VITO, MASSIMO GUARASCIO, NICOLA LEONE, GIUSEPPE MANCO, ALESSANDRO QUARTA, FRANCESCO RICCA e ETTORE RITACCO. "Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels". Theory and Practice of Logic Programming, 10 de julho de 2023, 1–17. http://dx.doi.org/10.1017/s1471068423000170.
Texto completo da fonteBeckmann, Pierre, Guillaume Köstner e Inês Hipólito. "An Alternative to Cognitivism: Computational Phenomenology for Deep Learning". Minds and Machines, 29 de junho de 2023. http://dx.doi.org/10.1007/s11023-023-09638-w.
Texto completo da fonteWu, Maonian, Bang Chen, Shaojun Zhu, Bo Zheng, Wei Peng e Mingyi Zhang. "Neuro-symbolic recommendation model based on logic query". Knowledge-Based Systems, dezembro de 2023, 111311. http://dx.doi.org/10.1016/j.knosys.2023.111311.
Texto completo da fonteRivas, Ariam, Diego Collarana, Maria Torrente e Maria-Esther Vidal. "A neuro-symbolic system over knowledge graphs for link prediction". Semantic Web, 7 de junho de 2023, 1–25. http://dx.doi.org/10.3233/sw-233324.
Texto completo da fonteGiunchiglia, Eleonora, Alex Tatomir, Mihaela Cătălina Stoian e Thomas Lukasiewicz. "CCN+: A Neuro-symbolic Framework for Deep Learning with Requirements". International Journal of Approximate Reasoning, janeiro de 2024, 109124. http://dx.doi.org/10.1016/j.ijar.2024.109124.
Texto completo da fonteSantos, Henrique, Ke Shen, Alice M. Mulvehill, Mayank Kejriwal e Deborah L. McGuinness. "A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense". Data Intelligence, 24 de outubro de 2023, 1–29. http://dx.doi.org/10.1162/dint_a_00234.
Texto completo da fonteMileo, Alessandra. "Towards a neuro-symbolic cycle for human-centered explainability". Neurosymbolic Artificial Intelligence, 28 de agosto de 2024, 1–13. http://dx.doi.org/10.3233/nai-240740.
Texto completo da fonteRoig Vilamala, Marc, Tianwei Xing, Harrison Taylor, Luis Garcia, Mani Srivastava, Lance Kaplan, Alun Preece, Angelika Kimmig e Federico Cerutti. "DeepProbCEP: A neuro-symbolic approach for complex event processing in adversarial settings". Expert Systems with Applications, dezembro de 2022, 119376. http://dx.doi.org/10.1016/j.eswa.2022.119376.
Texto completo da fonteEITER, THOMAS, NELSON HIGUERA, JOHANNES OETSCH e MICHAEL PRITZ. "A Neuro-Symbolic ASP Pipeline for Visual Question Answering". Theory and Practice of Logic Programming, 11 de julho de 2022, 1–16. http://dx.doi.org/10.1017/s1471068422000229.
Texto completo da fonteŠkrlj, Blaž, Jan Kralj, Janez Konc, Marko Robnik‐Šikonja e Nada Lavrač. "Deep node ranking for neuro‐symbolic structural node embedding and classification". International Journal of Intelligent Systems, 10 de setembro de 2021. http://dx.doi.org/10.1002/int.22651.
Texto completo da fonteAbdullah, Iram, Ali Javed, Khalid Mahmood Malik e Ghaus Malik. "DeepInfusion: A Dynamic Infusion based-Neuro-Symbolic AI Model for Segmentation of Intracranial Aneurysms". Neurocomputing, junho de 2023, 126510. http://dx.doi.org/10.1016/j.neucom.2023.126510.
Texto completo da fonteHersche, Michael, Mustafa Zeqiri, Luca Benini, Abu Sebastian e Abbas Rahimi. "A neuro-vector-symbolic architecture for solving Raven’s progressive matrices". Nature Machine Intelligence, 9 de março de 2023. http://dx.doi.org/10.1038/s42256-023-00630-8.
Texto completo da fonteVenigandla, Kamala, Navya Vemuri e Naveen Vemuri. "Hybrid Intelligence Systems Combining Human Expertise and AI/RPA for Complex Problem Solving". International Journal of Innovative Science and Research Technology (IJISRT), 5 de abril de 2024, 2066–75. http://dx.doi.org/10.38124/ijisrt/ijisrt24mar2039.
Texto completo da fonteHamilton, Kyle, Aparna Nayak, Bojan Božić e Luca Longo. "Is neuro-symbolic AI meeting its promises in natural language processing? A structured review". Semantic Web, 9 de novembro de 2022, 1–42. http://dx.doi.org/10.3233/sw-223228.
Texto completo da fonteChalvatzaki, Georgia, Ali Younes, Daljeet Nandha, An Thai Le, Leonardo F. R. Ribeiro e Iryna Gurevych. "Learning to reason over scene graphs: a case study of finetuning GPT-2 into a robot language model for grounded task planning". Frontiers in Robotics and AI 10 (15 de agosto de 2023). http://dx.doi.org/10.3389/frobt.2023.1221739.
Texto completo da fonteWickramarachchi, Ruwan, Cory Henson e Amit Sheth. "Knowledge-infused Learning for Entity Prediction in Driving Scenes". Frontiers in Big Data 4 (25 de novembro de 2021). http://dx.doi.org/10.3389/fdata.2021.759110.
Texto completo da fonteAbubakar, Hamza. "An optimal representation of Random Maximum kSatisfiability on a Hopfield Neural Network for High order logic(k 3)". Kuwait Journal of Science, 1 de dezembro de 2021. http://dx.doi.org/10.48129/kjs.11861.
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