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ORCIDArtur S. d'Avila Garcez
Artur d'Avila Garcez
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- affiliation: City University London, Department of Computer Science
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2020 – today
- 2025
[j31]Simon Odense, Artur d'Avila Garcez:
A semantic framework for neurosymbolic computation. Artif. Intell. 340: 104273 (2025)- [j30]Adrien Bennetot
, Ivan Donadello, Ayoub El Qadi, Mauro Dragoni, Thomas Frossard, Benedikt Wagner, Anna Saranti, Silvia Tulli, Maria Trocan, Raja Chatila, Andreas Holzinger, Artur d'Avila Garcez, Natalia Díaz Rodríguez:
A Practical Tutorial on Explainable AI Techniques. ACM Comput. Surv. 57(2): 50:1-50:44 (2025) - 2024
- [c100]Kwun Ho Ngan, James Phelan, Joe Townsend, Artur d'Avila Garcez:
Symbolic Knowledge Extraction and Distillation into Convolutional Neural Networks to Improve Medical Image Classification. IJCNN 2024: 1-8 - [c99]João Pedro Gandarela de Souza, Gerson Zaverucha, Artur S. d'Avila Garcez:
Hypergraph Neural Networks with Logic Clauses. IJCNN 2024: 1-8 - [c98]Qiqi Su, Christos Kloukinas, Artur d'Avila Garcez:
FocusLearn: Fully-Interpretable, High-Performance Modular Neural Networks for Time Series. IJCNN 2024: 1-8 - [e17]Tarek R. Besold, Artur d'Avila Garcez, Ernesto Jiménez-Ruiz, Roberto Confalonieri, Pranava Madhyastha, Benedikt Wagner:
Neural-Symbolic Learning and Reasoning - 18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14979, Springer 2024, ISBN 978-3-031-71166-4 [contents] - [e16]Tarek R. Besold, Artur d'Avila Garcez, Ernesto Jiménez-Ruiz, Roberto Confalonieri, Pranava Madhyastha, Benedikt Wagner:
Neural-Symbolic Learning and Reasoning - 18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14980, Springer 2024, ISBN 978-3-031-71169-5 [contents] - 2023
- [j29]Artur d'Avila Garcez, Luís C. Lamb:
Neurosymbolic AI: the 3rd wave. Artif. Intell. Rev. 56(11): 12387-12406 (2023) - [j28]Adam White, Kwun Ho Ngan, James Phelan, Kevin Ryan, Saman Sadeghi Afgeh, Constantino Carlos Reyes-Aldasoro, Artur S. d'Avila Garcez:
Contrastive counterfactual visual explanations with overdetermination. Mach. Learn. 112(9): 3497-3525 (2023) - [c97]Son N. Tran, Artur S. d'Avila Garcez:
Neurosymbolic Reasoning and Learning with Restricted Boltzmann Machines. AAAI 2023: 6558-6565 - [c96]Kwun Ho Ngan, James Phelan, Esma Mansouri-Benssassi, Joe Townsend, Artur S. d'Avila Garcez:
Closing the Neural-Symbolic Cycle: Knowledge Extraction, User Intervention and Distillation from Convolutional Neural Networks. NeSy 2023: 19-43 - [c95]Sofoklis Kyriakopoulos, Artur S. d'Avila Garcez:
Continual Reasoning: Non-monotonic Reasoning in Neurosymbolic AI using Continual Learning. NeSy 2023: 210-222 - [p4]Joe Townsend, Esma Mansouri-Benssassi, Kwun Ho Ngan, Artur d'Avila Garcez:
Discovering Visual Concepts and Rules in Convolutional Neural Networks. Compendium of Neurosymbolic Artificial Intelligence 2023: 337-372 - [e15]Artur S. d'Avila Garcez, Tarek R. Besold, Marco Gori, Ernesto Jiménez-Ruiz:
Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning, La Certosa di Pontignano, Siena, Italy, July 3-5, 2023. CEUR Workshop Proceedings 3432, CEUR-WS.org 2023 [contents] - [e14]Enrico Pontelli, Stefania Costantini, Carmine Dodaro, Sarah Alice Gaggl, Roberta Calegari, Artur S. d'Avila Garcez, Francesco Fabiano, Alessandra Mileo, Alessandra Russo, Francesca Toni:
Proceedings 39th International Conference on Logic Programming, ICLP 2023, Imperial College London, UK, 9th July 2023 - 15th July 2023. EPTCS 385, 2023 [contents] - [i35]Sofoklis Kyriakopoulos, Artur S. d'Avila Garcez:
Continual Reasoning: Non-Monotonic Reasoning in Neurosymbolic AI using Continual Learning. CoRR abs/2305.02171 (2023) - [i34]Adam White, Margarita Saranti, Artur S. d'Avila Garcez, Thomas M. H. Hope, Cathy J. Price, Howard Bowman:
Predicting recovery following stroke: deep learning, multimodal data and feature selection using explainable AI. CoRR abs/2310.19174 (2023) - [i33]Qiqi Su, Christos Kloukinas, Artur d'Avila Garcez:
Modular Neural Networks for Time Series Forecasting: Interpretability and Feature Selection using Attention. CoRR abs/2311.16834 (2023) - 2022
- [j27]Samy Badreddine, Artur S. d'Avila Garcez, Luciano Serafini, Michael Spranger:
Logic Tensor Networks. Artif. Intell. 303: 103649 (2022) - [c94]Benedikt Wagner, Artur S. d'Avila Garcez:
Neural-Symbolic Reasoning Under Open-World and Closed-World Assumptions. AAAI Spring Symposium: MAKE 2022 - [c93]Kwun Ho Ngan, Artur S. d'Avila Garcez, Joseph Townsend:
Extracting Meaningful High-Fidelity Knowledge from Convolutional Neural Networks. IJCNN 2022: 1-17 - [c92]Harald Strömfelt, Luke Dickens, Artur S. d'Avila Garcez, Alessandra Russo:
Formalizing Consistency and Coherence of Representation Learning. NeurIPS 2022 - [e13]Artur S. d'Avila Garcez, Ernesto Jiménez-Ruiz:
Proceedings of the 16th International Workshop on Neural-Symbolic Learning and Reasoning as part of the 2nd International Joint Conference on Learning & Reasoning (IJCLR 2022), Cumberland Lodge, Windsor Great Park, UK, September 28-30, 2022. CEUR Workshop Proceedings 3212, CEUR-WS.org 2022 [contents] - [i32]Breno W. Carvalho, Artur d'Avila Garcez, Luís C. Lamb:
Graph-based Neural Modules to Inspect Attention-based Architectures: A Position Paper. CoRR abs/2210.07117 (2022) - [i31]Simon Odense, Artur d'Avila Garcez:
A Semantic Framework for Neural-Symbolic Computing. CoRR abs/2212.12050 (2022) - 2021
- [j26]Chris Percy, Simo Dragicevic, Sanjoy Sarkar, Artur S. d'Avila Garcez:
Accountability in AI: From principles to industry-specific accreditation. AI Commun. 34(3): 181-196 (2021) - [c91]Breno W. Carvalho, Artur S. d'Avila Garcez, Luís C. Lamb:
Graph-Based Neural Modules to Inspect Attention-Based Architectures, A Position Paper. TFSOCTAI@AAAI Fall Symposium 2021 - [c90]Benedikt Wagner, Artur S. d'Avila Garcez:
Neural-Symbolic Integration for Fairness in AI. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2021 - [c89]Harald Strömfelt, Luke Dickens, Artur S. d'Avila Garcez, Alessandra Russo:
Coherent and Consistent Relational Transfer Learning with Auto-encoders. NeSy 2021: 176-192 - [p3]Tarek R. Besold, Artur S. d'Avila Garcez, Sebastian Bader, Howard Bowman, Pedro M. Domingos, Pascal Hitzler, Kai-Uwe Kühnberger, Luís C. Lamb, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon, Gerson Zaverucha:
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. Neuro-Symbolic Artificial Intelligence 2021: 1-51 - [p2]Luciano Serafini, Artur S. d'Avila Garcez, Samy Badreddine, Ivan Donadello, Michael Spranger, Federico Bianchi:
Logic Tensor Networks: Theory and Applications. Neuro-Symbolic Artificial Intelligence 2021: 370-394 - [e12]Artur S. d'Avila Garcez, Ernesto Jiménez-Ruiz:
Proceedings of the 15th International Workshop on Neural-Symbolic Learning and Reasoning as part of the 1st International Joint Conference on Learning & Reasoning (IJCLR 2021), Virtual conference, October 25-27, 2021. CEUR Workshop Proceedings 2986, CEUR-WS.org 2021 [contents] - [i30]Adam White, Kwun Ho Ngan, James Phelan, Saman Sadeghi Afgeh, Kevin Ryan, Constantino Carlos Reyes-Aldasoro, Artur S. d'Avila Garcez:
Contrastive Counterfactual Visual Explanations With Overdetermination. CoRR abs/2106.14556 (2021) - [i29]Adam White, Artur S. d'Avila Garcez:
Counterfactual Instances Explain Little. CoRR abs/2109.09809 (2021) - [i28]Charitos Charitou, Simo Dragicevic, Artur S. d'Avila Garcez:
Synthetic Data Generation for Fraud Detection using GANs. CoRR abs/2109.12546 (2021) - [i27]Chris Percy, Simo Dragicevic, Sanjoy Sarkar, Artur S. d'Avila Garcez:
Accountability in AI: From Principles to Industry-specific Accreditation. CoRR abs/2110.09232 (2021) - [i26]Adrien Bennetot, Ivan Donadello, Ayoub El Qadi, Mauro Dragoni, Thomas Frossard, Benedikt Wagner, Anna Saranti, Silvia Tulli, Maria Trocan, Raja Chatila, Andreas Holzinger, Artur S. d'Avila Garcez, Natalia Díaz Rodríguez:
A Practical Tutorial on Explainable AI Techniques. CoRR abs/2111.14260 (2021) - [i25]Son N. Tran, Artur S. d'Avila Garcez:
Logical Boltzmann Machines. CoRR abs/2112.05841 (2021) - [i24]Benedikt Wagner, Artur S. d'Avila Garcez:
Neural-Symbolic Integration for Interactive Learning and Conceptual Grounding. CoRR abs/2112.11805 (2021) - 2020
- [j25]Son N. Tran, Ngo Tung Son, Artur S. d'Avila Garcez:
Probabilistic approaches for music similarity using restricted Boltzmann machines. Neural Comput. Appl. 32(8): 3999-4008 (2020) - [j24]Son N. Tran, Artur S. d'Avila Garcez, Tillman Weyde, Jie Yin, Qing Zhang, Mohan Karunanithi:
Sequence Classification Restricted Boltzmann Machines With Gated Units. IEEE Trans. Neural Networks Learn. Syst. 31(11): 4806-4815 (2020) - [c88]Christian Percy, Artur S. d'Avila Garcez, Simo Dragicevic, Sanjoy Sarkar:
Lessons Learned from Problem Gambling Classification: Indirect Discrimination and Algorithmic Fairness. AI4SG@AAAI Fall Symposium 2020 - [c87]Adam White, Artur S. d'Avila Garcez:
Measurable Counterfactual Local Explanations for Any Classifier. ECAI 2020: 2529-2535 - [c86]Henrique Lemos, Pedro H. C. Avelar, Marcelo O. R. Prates, Artur S. d'Avila Garcez, Luís C. Lamb:
Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases. ICANN (1) 2020: 647-659 - [c85]Luís C. Lamb, Artur S. d'Avila Garcez, Marco Gori, Marcelo O. R. Prates, Pedro H. C. Avelar, Moshe Y. Vardi:
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective. IJCAI 2020: 4877-4884 - [c84]Charitos Charitou, Artur S. d'Avila Garcez, Simo Dragicevic:
Semi-supervised GANs for Fraud Detection*. IJCNN 2020: 1-8 - [c83]Régis Riveret, Son N. Tran, Artur S. d'Avila Garcez:
Neuro-Symbolic Probabilistic Argumentation Machines. KR 2020: 871-881 - [c82]Kwun Ho Ngan, Artur S. d'Avila Garcez, Karen M. Knapp, Andy Appelboam, Constantino Carlos Reyes-Aldasoro:
A Machine Learning Approach for Colles' Fracture Treatment Diagnosis. MIUA 2020: 319-330 - [i23]Luís C. Lamb, Artur S. d'Avila Garcez, Marco Gori, Marcelo O. R. Prates, Pedro H. C. Avelar, Moshe Y. Vardi:
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective. CoRR abs/2003.00330 (2020) - [i22]Simon Odense, Artur S. d'Avila Garcez:
Layerwise Knowledge Extraction from Deep Convolutional Networks. CoRR abs/2003.09000 (2020) - [i21]Henrique Lemos, Pedro H. C. Avelar, Marcelo O. R. Prates, Luís C. Lamb, Artur S. d'Avila Garcez:
Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases. CoRR abs/2005.02525 (2020) - [i20]Harald Strömfelt, Luke Dickens, Artur S. d'Avila Garcez, Alessandra Russo:
On the Transferability of VAE Embeddings using Relational Knowledge with Semi-Supervision. CoRR abs/2011.07137 (2020) - [i19]Artur S. d'Avila Garcez, Luís C. Lamb:
Neurosymbolic AI: The 3rd Wave. CoRR abs/2012.05876 (2020) - [i18]Samy Badreddine, Artur S. d'Avila Garcez, Luciano Serafini, Michael Spranger:
Logic Tensor Networks. CoRR abs/2012.13635 (2020)
2010 – 2019
- 2019
- [j23]Artur S. d'Avila Garcez, Tarek R. Besold:
Editorial. FLAP 6(4): 609-610 (2019) - [j22]Artur S. d'Avila Garcez, Marco Gori, Luís C. Lamb, Luciano Serafini, Michael Spranger, Son N. Tran:
Neural-symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning. FLAP 6(4): 611-632 (2019) - [j21]Akira Hirose, Alessio Micheli, Artur S. d'Avila Garcez, Choon Ki Ahn, Gang Pan, Hamid Reza Karimi, Jianbing Shen, José de Jesús Rubio, Lei Zhang, Lingjia Liu, Lorenzo Livi, Nian Zhang, Nishchal K. Verma, Pedro Antonio Gutiérrez, Qi Tian, Qinglai Wei, Seiichi Ozawa, Stuart H. Rubin, Wei-Neng Chen, Xi Li, Xiaofeng Liao, Youmin Zhang, Zhen Ni, Haibo He:
Editorial: Booming of Neural Networks and Learning Systems. IEEE Trans. Neural Networks Learn. Syst. 30(1): 2-10 (2019) - [c81]Edjard Mota, Jacob M. Howe, Ana Schramm, Artur S. d'Avila Garcez:
Efficient Predicate Invention using Shared NeMuS. NeSy@IJCAI 2019 - [e11]Derek Doran, Artur S. d'Avila Garcez, Freddy Lécué:
Proceedings of the 2019 International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2019), Annual workshop of the Neural-Symbolic Learning and Reasoning Association, Macao, China, August 12, 2019. 2019 [contents] - [i17]Artur S. d'Avila Garcez, Marco Gori, Luís C. Lamb, Luciano Serafini, Michael Spranger, Son N. Tran:
Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning. CoRR abs/1905.06088 (2019) - [i16]Edjard Mota, Jacob M. Howe, Ana Schramm, Artur S. d'Avila Garcez:
Efficient predicate invention using shared "NeMuS". CoRR abs/1906.06455 (2019) - [i15]Adam White, Artur S. d'Avila Garcez:
Measurable Counterfactual Local Explanations for Any Classifier. CoRR abs/1908.03020 (2019) - [i14]Daniel Philps, Artur S. d'Avila Garcez, Tillman Weyde:
Making Good on LSTMs Unfulfilled Promise. CoRR abs/1911.04489 (2019) - 2018
- [j20]Hazrat Ali, Son Ngoc Tran, Emmanouil Benetos, Artur S. d'Avila Garcez:
Speaker recognition with hybrid features from a deep belief network. Neural Comput. Appl. 29(6): 13-19 (2018) - [j19]Son Ngoc Tran, Artur S. d'Avila Garcez:
Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks. IEEE Trans. Neural Networks Learn. Syst. 29(2): 246-258 (2018) - [i13]Artur S. d'Avila Garcez, Aimore Resende Riquetti Dutra, Eduardo Alonso:
Towards Symbolic Reinforcement Learning with Common Sense. CoRR abs/1804.08597 (2018) - [i12]Daniel Philps, Tillman Weyde, Artur S. d'Avila Garcez, Roy Batchelor:
Continual Learning Augmented Investment Decisions. CoRR abs/1812.02340 (2018) - 2017
- [j18]Tarek R. Besold, Artur S. d'Avila Garcez, Keith Stenning, Leendert W. N. van der Torre, Michiel van Lambalgen:
Reasoning in Non-probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples. Minds Mach. 27(1): 37-77 (2017) - [c80]Srikanth Cherla, Son Ngoc Tran, Artur S. d'Avila Garcez, Tillman Weyde:
Generalising the Discriminative Restricted Boltzmann Machines. ICANN (2) 2017: 111-119 - [c79]Simon Odense, Artur S. d'Avila Garcez:
Extracting M of N Rules from Restricted Boltzmann Machines. ICANN (2) 2017: 120-127 - [c78]Ivan Donadello, Luciano Serafini, Artur S. d'Avila Garcez:
Logic Tensor Networks for Semantic Image Interpretation. IJCAI 2017: 1596-1602 - [c77]Arthur Jack Russell, Emmanouil Benetos, Artur S. d'Avila Garcez:
On the memory properties of recurrent neural models. IJCNN 2017: 2596-2603 - [c76]Aimore R. R. Dutra, Artur S. d'Avila Garcez:
A Comparison between Deep Q-Networks and Deep Symbolic Reinforcement Learning. NeSy 2017 - [c75]Edjard de Souza Mota, Jacob M. Howe, Artur S. d'Avila Garcez:
Inductive Learning in Shared Neural Multi-Spaces. NeSy 2017 - [c74]Simon Odense, Artur S. d'Avila Garcez:
Confidence Values and Compact Rule Extraction From Probabilistic Neural Networks. NeSy 2017 - [c73]Ana Carolina Melik Schramm, Edjard de Souza Mota, Jacob M. Howe, Artur S. d'Avila Garcez:
Category-based Inductive Learning in Shared NeMuS. NeSy 2017 - [c72]Milena Rodrigues Tenorio, Edjard de Souza Mota, Jacob M. Howe, Artur S. d'Avila Garcez:
Learning about Actions and Events in Shared NeMuS. NeSy 2017 - [c71]Luciano Serafini, Ivan Donadello, Artur S. d'Avila Garcez:
Learning and reasoning in logic tensor networks: theory and application to semantic image interpretation. SAC 2017: 125-130 - [e10]Tarek R. Besold, Artur S. d'Avila Garcez, Isaac Noble:
Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, NeSy 2017, London, UK, July 17-18, 2017. CEUR Workshop Proceedings 2003, CEUR-WS.org 2017 [contents] - [i11]Tarek R. Besold, Artur S. d'Avila Garcez, Keith Stenning, Leendert W. N. van der Torre, Michiel van Lambalgen:
Reasoning in Non-Probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples. CoRR abs/1701.05226 (2017) - [i10]Ivan Donadello, Luciano Serafini, Artur S. d'Avila Garcez:
Logic Tensor Networks for Semantic Image Interpretation. CoRR abs/1705.08968 (2017) - [i9]Son N. Tran, Srikanth Cherla, Artur S. d'Avila Garcez, Tillman Weyde:
The Recurrent Temporal Discriminative Restricted Boltzmann Machines. CoRR abs/1710.02245 (2017) - [i8]Tarek R. Besold, Artur S. d'Avila Garcez, Sebastian Bader, Howard Bowman, Pedro M. Domingos, Pascal Hitzler, Kai-Uwe Kühnberger, Luís C. Lamb, Daniel Lowd, Priscila Machado Vieira Lima, Leo de Penning, Gadi Pinkas, Hoifung Poon, Gerson Zaverucha:
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. CoRR abs/1711.03902 (2017) - [i7]Tarek R. Besold, Artur S. d'Avila Garcez, Luís C. Lamb:
Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192). Dagstuhl Reports 7(5): 56-83 (2017) - 2016
- [j17]Avelino Forechi, Alberto F. De Souza, Jorcy de Oliveira Neto, Edilson de Aguiar, Claudine Badue, Artur S. d'Avila Garcez, Thiago Oliveira-Santos:
Fat-Fast VG-RAM WNN: A high performance approach. Neurocomputing 183: 56-69 (2016) - [c70]Luciano Serafini, Artur S. d'Avila Garcez:
Learning and Reasoning with Logic Tensor Networks. AI*IA 2016: 334-348 - [c69]Chris Percy, Artur S. d'Avila Garcez, Simo Dragicevic, Manoel V. M. França, Greg G. Slabaugh, Tillman Weyde:
The Need for Knowledge Extraction: Understanding Harmful Gambling Behavior with Neural Networks. ECAI 2016: 974-981 - [c68]Son Ngoc Tran, Artur S. d'Avila Garcez:
Adaptive Transferred-profile Likelihood Learning. IJCNN 2016: 2687-2692 - [c67]Luciano Serafini, Artur S. d'Avila Garcez:
Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge. NeSy@HLAI 2016 - [c66]Özgür Yilmaz, Artur S. d'Avila Garcez, Daniel L. Silver:
A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies. NeSy@HLAI 2016 - [c65]Sanjoy Sarkar, Tillman Weyde, Artur S. d'Avila Garcez, Gregory G. Slabaugh, Simo Dragicevic, Chris Percy:
Accuracy and Interpretability Trade-Offs in Machine Learning Applied to Safer Gambling. CoCo@NIPS 2016 - [e9]Tarek Richard Besold, Artur S. d'Avila Garcez, Gary F. Marcus, Risto Miikkulainen:
Proceedings of the NIPS Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches co-located with the 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), Montreal, Canada, December 11-12, 2015. CEUR Workshop Proceedings 1583, CEUR-WS.org 2016 [contents] - [e8]Tarek Richard Besold, Antoine Bordes, Artur S. d'Avila Garcez, Greg Wayne:
Proceedings of the Workshop on Cognitive Computation: Integrating neural and symbolic approaches 2016 co-located with the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain, December 9, 2016. CEUR Workshop Proceedings 1773, CEUR-WS.org 2016 [contents] - [i6]Srikanth Cherla, Son N. Tran, Tillman Weyde, Artur S. d'Avila Garcez:
Generalising the Discriminative Restricted Boltzmann Machine. CoRR abs/1604.01806 (2016) - [i5]Luciano Serafini, Artur S. d'Avila Garcez:
Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge. CoRR abs/1606.04422 (2016) - 2015
- [c64]Manoel Vitor Macedo França, Gerson Zaverucha, Artur S. d'Avila Garcez:
Neural Relational Learning Through Semi-Propositionalization of Bottom Clauses. AAAI Spring Symposia 2015 - [c63]Artur S. d'Avila Garcez, Tarek R. Besold, Luc De Raedt, Peter Földiák, Pascal Hitzler, Thomas Icard, Kai-Uwe Kühnberger, Luís C. Lamb, Risto Miikkulainen, Daniel L. Silver:
Neural-Symbolic Learning and Reasoning: Contributions and Challenges. AAAI Spring Symposia 2015 - [c62]Tarek Richard Besold, Kai-Uwe Kühnberger, Artur S. d'Avila Garcez, Alessandro Saffiotti, Martin H. Fischer, Alan Bundy:
Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognition. AGI 2015: 35-45 - [c61]Siddharth Sigtia, Emmanouil Benetos, Nicolas Boulanger-Lewandowski, Tillman Weyde, Artur S. d'Avila Garcez, Simon Dixon:
A hybrid recurrent neural network for music transcription. ICASSP 2015: 2061-2065 - [c60]Srikanth Cherla, Son Ngoc Tran, Artur S. d'Avila Garcez, Tillman Weyde:
Discriminative learning and inference in the Recurrent Temporal RBM for melody modelling. IJCNN 2015: 1-8 - [c59]Alan Perotti, Artur S. d'Avila Garcez, Guido Boella:
Neural-symbolic monitoring and adaptation. IJCNN 2015: 1-8 - [c58]Son Ngoc Tran, Artur S. d'Avila Garcez:
Efficient representation ranking for transfer learning. IJCNN 2015: 1-8 - [c57]Srikanth Cherla, Son N. Tran, Tillman Weyde, Artur S. d'Avila Garcez:
Hybrid Long- and Short-Term Models of Folk Melodies. ISMIR 2015: 584-590 - [c56]Shijing Guo, Abdul V. Roudsari, Artur S. d'Avila Garcez:
Modelling Clinical Diagnostic Errors: A System Dynamics Approach. ITCH 2015: 160-164 - [c55]Shijing Guo, Abdul V. Roudsari, Artur S. d'Avila Garcez:
A System Dynamics Approach to Analyze Laboratory Test Errors. MIE 2015: 266-270 - [c54]Manoel Vitor Macedo França, Artur S. d'Avila Garcez, Gerson Zaverucha:
Relational Knowledge Extraction from Neural Networks. CoCo@NIPS 2015 - [c53]Alan Perotti, Guido Boella, Artur S. d'Avila Garcez:
Runtime Verification Through Forward Chaining. RV 2015: 185-200 - 2014
- [j16]Artur S. d'Avila Garcez, Dov M. Gabbay, Luís C. Lamb:
A neural cognitive model of argumentation with application to legal inference and decision making. J. Appl. Log. 12(2): 109-127 (2014) - [j15]Manoel V. M. França, Gerson Zaverucha, Artur S. d'Avila Garcez:
Fast relational learning using bottom clause propositionalization with artificial neural networks. Mach. Learn. 94(1): 81-104 (2014) - [c52]Leo de Penning, Artur S. d'Avila Garcez, Luís C. Lamb, John-Jules Ch. Meyer:
Neural-symbolic cognitive agents: architecture, theory and application. AAMAS 2014: 1621-1622 - [c51]Son Ngoc Tran, Artur S. d'Avila Garcez:
Low-Cost Representation for Restricted Boltzmann Machines. ICONIP (1) 2014: 69-77 - [c50]Leo de Penning, Artur S. d'Avila Garcez, Luís C. Lamb, Arjan Stuiver, John-Jules Ch. Meyer:
Applying Neural-Symbolic Cognitive Agents in Intelligent Transport Systems to reduce CO2 emissions. IJCNN 2014: 55-62 - [c49]Son Ngoc Tran, Emmanouil Benetos, Artur S. d'Avila Garcez:
Learning motion-difference features using Gaussian restricted Boltzmann machines for efficient human action recognition. IJCNN 2014: 2123-2129 - [c48]Alan Perotti, Artur S. d'Avila Garcez, Guido Boella:
Neural Networks for Runtime Verification. IJCNN 2014: 2637-2644 - [c47]Siddharth Sigtia, Emmanouil Benetos, Srikanth Cherla, Tillman Weyde, Artur S. d'Avila Garcez, Simon Dixon:
An RNN-based Music Language Model for Improving Automatic Music Transcription. ISMIR 2014: 53-58 - [c46]Srikanth Cherla, Tillman Weyde, Artur S. d'Avila Garcez:
Multiple Viewpiont Melodic Prediction with Fixed-Context Neural Networks. ISMIR 2014: 101-106 - [c45]Shijing Guo, Abdul V. Roudsari, Artur S. d'Avila Garcez:
A Causal Loop Approach to the Study of Diagnostic Errors. MIE 2014: 73-77 - [c44]Son N. Tran, Daniel Wolff, Tillman Weyde, Artur S. d'Avila Garcez:
Feature Preprocessing with Restricted Boltzmann Machines for Music Similarity Learning. Semantic Audio 2014 - [c43]Alan Perotti, Guido Boella, Artur S. d'Avila Garcez:
Scalable Process Monitoring through Rules and Neural Networks. SIMPDA 2014: 108-122 - [c42]Alan Perotti, Guido Boella, Artur S. d'Avila Garcez:
Runtime Verification Through Forward Chaining. HCVS 2014: 68-81 - [i4]Siddharth Sigtia, Emmanouil Benetos, Nicolas Boulanger-Lewandowski, Tillman Weyde, Artur S. d'Avila Garcez, Simon Dixon:
A Hybrid Recurrent Neural Network For Music Transcription.