Applying the connectionist inductive learning and logic programming system to power system diagnosis. - Artur S. d'Avila Garcez; Gerson Zaverucha; Victor Navoarro Araujo Lemos da Silva (ICNN, 1997)

Inducing Relational Concepts with Neural Networks via the LINUS System. - Rodrigo Basilio; Gerson Zaverucha; Artur S. d'Avila Garcez (ICONIP, 1998)

The Connectionist Inductive Learning and Logic Programming System. - Artur S. d'Avila Garcez; Gerson Zaverucha (Appl. Intell., 1999)

An Analysis-Revision Cycle to Evolve Requirements Specifications. - Artur S. d'Avila Garcez; Alessandra Russo; Bashar Nuseibeh; Jeff Kramer (ASE, 2001)

Symbolic knowledge extraction from trained neural networks: A sound approach. - Artur S. d'Avila Garcez; Krysia Broda; Dov M. Gabbay (Artif. Intell., 2001)

Neural-symbolic learning systems - foundations and applications. - Artur S. d'Avila Garcez; Krysia Broda; Dov M. Gabbay (Springer, 2002)

Distributed Knowledge Representation in Neural-Symbolic Learning Systems: A Case Study. - Artur S. d'Avila Garcez; Luís C. Lamb; Krysia Broda; Dov M. Gabbay (FLAIRS, 2003)

Neural-Symbolic Intuitionistic Reasoning. - Artur S. d'Avila Garcez; Luís C. Lamb; Dov M. Gabbay (HIS, 2003)

Reasoning about Time and Knowledge in Neural Symbolic Learning Systems. - Artur S. d'Avila Garcez; Luís C. Lamb (NIPS, 2003)

Revising Rules to Capture Requirements Traceability Relations: A Machine Learning Approach. - George Spanoudakis; Artur S. d'Avila Garcez; Andrea Zisman (SEKE, 2003)

Combining abductive reasoning and inductive learning to evolve requirements specifications. - Artur S. d'Avila Garcez; Alessandra Russo; Bashar Nuseibeh; Jeff Kramer (IEE Proc. Softw., 2003)

Fibring Neural Networks. - Artur S. d'Avila Garcez; Dov M. Gabbay (AAAI, 2004)

Towards a Connectionist Argumentation Framework. - Artur S. d'Avila Garcez; Dov M. Gabbay; Luís C. Lamb (ECAI, 2004)

Argumentation Neural Networks. - Artur S. d'Avila Garcez; Dov M. Gabbay; Luís C. Lamb (ICONIP, 2004)

Reasoning About Requirements Evolution Using Clustered Belief Revision. - Odinaldo Rodrigues; Artur S. d'Avila Garcez; Alessandra Russo (SBIA, 2004)

Applying connectionist modal logics to distributed knowledge representation problems. - Artur S. d'Avila Garcez; Luís C. Lamb; Krysia Broda; Dov M. Gabbay (Int. J. Artif. Intell. Tools, 2004)

Journal of Applied Logic Special Volume on Neural-Symbolic Systems. - Artur S. d'Avila Garcez; Dov M. Gabbay; Steffen Hölldobler; John G. Taylor (J. Appl. Log., 2004)

Neural-Symbolic Systems and the Case for Non-Classical Reasoning. - Artur S. d'Avila Garcez; Luís C. Lamb (We Will Show Them! (1), 2005)

Fewer Epistemological Challenges for Connectionism. - Artur S. d'Avila Garcez (CiE, 2005)

Computing First-Order Logic Programs by Fibring Artificial Neural Networks. - Sebastian Bader 001; Artur S. d'Avila Garcez; Pascal Hitzler (FLAIRS, 2005)

A Connectionist Model for Constructive Modal Reasoning. - Artur S. d'Avila Garcez; Luís C. Lamb; Dov M. Gabbay (NIPS, 2005)

Value-based Argumentation Frameworks as Neural-symbolic Learning Systems. - Artur S. d'Avila Garcez; Dov M. Gabbay; Luís C. Lamb (J. Log. Comput., 2005)

Combining Architectures for Temporal Learning in Neural-Symbolic Systems. - Rafael V. Borges; Luís C. Lamb; Artur S. d'Avila Garcez (HIS, 2006)

Improving VG-RAM Neural Networks Performance Using Knowledge Correlation. - Raphael V. Carneiro; Stiven Schwanz Dias; Dijalma Fardin; Hallysson Oliveira; Artur S. d'Avila Garcez; Alberto Ferreira de Souza (ICONIP (1), 2006)

A Connectionist Computational Model for Epistemic and Temporal Reasoning. - Artur S. d'Avila Garcez; Luís C. Lamb (Neural Comput., 2006)

Connectionist computations of intuitionistic reasoning. - Artur S. d'Avila Garcez; Luís C. Lamb; Dov M. Gabbay (Theor. Comput. Sci., 2006)

A Connectionist Cognitive Model for Temporal Synchronisation and Learning. - Luís C. Lamb; Rafael V. Borges; Artur S. d'Avila Garcez (AAAI, 2007)

Towards Reasoning about the Past in Neural-symbolic Systems. - Rafael V. Borges; Luís C. Lamb; Artur S. d'Avila Garcez (NeSy, 2007)

Editorial. - Artur S. d'Avila Garcez; Pascal Hitzler; Guglielmo Tamburrini (NeSy, 2007)

Reasoning and Learning About Past Temporal Knowledge in Connectionist Models. - Rafael V. Borges; Luís C. Lamb; Artur S. d'Avila Garcez (IJCNN, 2007)

Connectionist modal logic: Representing modalities in neural networks. - Artur S. d'Avila Garcez; Luís C. Lamb; Dov M. Gabbay (Theor. Comput. Sci., 2007)

Advances in Neural-Symbolic Learning Systems: Modal and Temporal Reasoning. - Artur S. d'Avila Garcez (Perspectives of Neural-Symbolic Integration, 2007)

Symbolic Knowledge Extraction from Support Vector Machines: A Geometric Approach. - Lu Ren; Artur S. d'Avila Garcez (ICONIP (2), 2008)

Preface: Reinforcement Learning. - Kostas Stathis; Artur S. d'Avila Garcez; Robert Givan (J. Algorithms, 2009)

Logical Modes of Attack in Argumentation Networks. - Dov M. Gabbay; Artur S. d'Avila Garcez (Stud Logica, 2009)

Neural-Symbolic Cognitive Reasoning - Artur S. d'Avila Garcez; Luís C. Lamb; Dov M. Gabbay (Springer, 2009)

Neurons and Symbols: A Manifesto. - Artur S. d'Avila Garcez (Learning paradigms in dynamic environments, 2010)

Representing, Learning and Extracting Temporal Knowledge from Neural Networks: A Case Study. - Rafael V. Borges; Artur S. d'Avila Garcez; Luís C. Lamb (ICANN (2), 2010)

Neuro-symbolic Representation of Logic Programs Defining Infinite Sets. - Ekaterina Komendantskaya; Krysia Broda; Artur S. d'Avila Garcez (ICANN (1), 2010)

First-order logic learning in Artificial Neural Networks. - Mathieu Guillame-Bert; Krysia Broda; Artur S. d'Avila Garcez (IJCNN, 2010)

SOAR - Sparse Oracle-based Adaptive Rule extraction: Knowledge extraction from large-scale datasets to detect credit card fraud. - Nick F. Ryman-Tubb; Artur S. d'Avila Garcez (IJCNN, 2010)

Integrating model verification and self-adaptation. - Rafael V. Borges; Artur S. d'Avila Garcez; Luís C. Lamb (ASE, 2010)

Reports of the AAAI 2010 Conference Workshops. - David W. Aha; Mark S. Boddy; Vadim Bulitko; Artur S. d'Avila Garcez; Prashant Doshi; Stefan Edelkamp; Christopher W. Geib; Piotr J. Gmytrasiewicz; Robert P. Goldman; Pascal Hitzler; Charles L. Isbell Jr.; Darsana P. Josyula; et al. (AI Mag., 2010)

Neural symbolic architecture for normative agents. - Guido Boella; Silvano Colombo Tosatto; Artur S. d'Avila Garcez; Valerio Genovese; Dino Ienco; Leendert W. N. van der Torre (AAMAS, 2011)

Neural-Symbolic Cognitive Agents: Architecture and Theory. - Leo de Penning; Artur S. d'Avila Garcez; Luís C. Lamb; John-Jules Ch. Meyer (ICCSW, 2011)

Learning to adapt requirements specifications of evolving systems. - Rafael V. Borges; Artur S. d'Avila Garcez; Luís C. Lamb; Bashar Nuseibeh (ICSE, 2011)

A Neural-Symbolic Cognitive Agent for Online Learning and Reasoning. - Leo de Penning; Artur S. d'Avila Garcez; Luís C. Lamb; John-Jules Ch. Meyer (IJCAI, 2011)

Embedding Normative Reasoning into Neural Symbolic Systems. - Guido Boella; Silvano Colombo Tosatto; Artur S. d'Avila Garcez; Valerio Genovese; Leon van der Torre (NeSy, 2011)

Learning and Representing Temporal Knowledge in Recurrent Networks. - Rafael V. Borges; Artur S. d'Avila Garcez; Luís C. Lamb (IEEE Trans. Neural Networks, 2011)

Learning and reasoning about norms using neural-symbolic systems. - Guido Boella; Silvano Colombo Tosatto; Artur S. d'Avila Garcez; Valerio Genovese; Alan Perotti; Leendert W. N. van der Torre (AAMAS, 2012)

Multi-instance learning using recurrent neural networks. - Artur S. d'Avila Garcez; Gerson Zaverucha (IJCNN, 2012)

Organizers. - Artur d'Avila Garcez (NeSy@AAAI, 2012)

Preface. - Artur d'Avila Garcez (NeSy@AAAI, 2012)

A Neural-Symbolic Cognitive Agent with a Mind's Eye. - H. L. H. de Penning; R. J. M. den Hollander; Henri Bouma; Gertjan J. Burghouts; Artur S. d'Avila Garcez (NeSy@AAAI, 2012)

Neural-Symbolic Rule-Based Monitoring. - Alan Perotti; Artur d'Avila Garcez; Guido Boella; Daniele Rispoli (NeSy@AAAI, 2012)

Reports of the AAAI 2012 Conference Workshops. - Vikas Agrawal; Jorge A. Baier; Kostas E. Bekris; Yiling Chen 001; Artur S. d'Avila Garcez; Pascal Hitzler; Patrik Haslum; Dietmar Jannach; Edith Law; Freddy Lécué; Luís C. Lamb; Cynthia Matuszek; et al. (AI Mag., 2012)

Relational Knowledge Extraction from Attribute-Value Learners. - Manoel V. M. França; Artur S. d'Avila Garcez; Gerson Zaverucha (ICCSW, 2013)

Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents. - Leo de Penning; Artur S. d'Avila Garcez; John-Jules Ch. Meyer (ICCSW, 2013)

A Distributed Model For Multiple-Viewpoint Melodic Prediction. - Srikanth Cherla; Tillman Weyde; Artur S. d'Avila Garcez; Marcus T. Pearce (ISMIR, 2013)

Adaptive Feature Ranking for Unsupervised Transfer Learning. - Son N. Tran; Artur S. d'Avila Garcez (CoRR, 2013)

Neural-symbolic cognitive agents: architecture, theory and application. - Leo de Penning; Artur S. d'Avila Garcez; Luís C. Lamb; John-Jules Ch. Meyer (AAMAS, 2014)

Low-Cost Representation for Restricted Boltzmann Machines. - Son Ngoc Tran; Artur S. d'Avila Garcez (ICONIP (1), 2014)

Applying Neural-Symbolic Cognitive Agents in Intelligent Transport Systems to reduce CO2 emissions. - Leo de Penning; Artur S. d'Avila Garcez; Luís C. Lamb; Arjan Stuiver; John-Jules Ch. Meyer (IJCNN, 2014)

Neural Networks for Runtime Verification. - Alan Perotti; Artur S. d'Avila Garcez; Guido Boella (IJCNN, 2014)

Learning motion-difference features using Gaussian restricted Boltzmann machines for efficient human action recognition. - Son Ngoc Tran; Emmanouil Benetos; Artur S. d'Avila Garcez (IJCNN, 2014)

Multiple Viewpiont Melodic Prediction with Fixed-Context Neural Networks. - Srikanth Cherla; Tillman Weyde; Artur S. d'Avila Garcez (ISMIR, 2014)

An RNN-based Music Language Model for Improving Automatic Music Transcription. - Siddharth Sigtia; Emmanouil Benetos; Srikanth Cherla; Tillman Weyde; Artur S. d'Avila Garcez; Simon Dixon (ISMIR, 2014)

A Causal Loop Approach to the Study of Diagnostic Errors. - Shijing Guo; Abdul V. Roudsari; Artur S. d'Avila Garcez (MIE, 2014)

Feature Preprocessing with Restricted Boltzmann Machines for Music Similarity Learning. - Son N. Tran; Daniel Wolff; Tillman Weyde; Artur S. d'Avila Garcez (Semantic Audio, 2014)

Scalable Process Monitoring through Rules and Neural Networks. - Alan Perotti; Guido Boella; Artur S. d'Avila Garcez (SIMPDA, 2014)

Runtime Verification Through Forward Chaining. - Alan Perotti; Guido Boella; Artur S. d'Avila Garcez (HCVS, 2014)

Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381). - Artur S. d'Avila Garcez; Marco Gori; Pascal Hitzler; Luís C. Lamb (Dagstuhl Reports, 2014)

A neural cognitive model of argumentation with application to legal inference and decision making. - Artur S. d'Avila Garcez; Dov M. Gabbay; Luís C. Lamb (J. Appl. Log., 2014)

Fast relational learning using bottom clause propositionalization with artificial neural networks. - Manoel V. M. França; Gerson Zaverucha; Artur S. d'Avila Garcez (Mach. Learn., 2014)

Neural Relational Learning Through Semi-Propositionalization of Bottom Clauses. - Manoel Vitor Macedo França; Gerson Zaverucha; Artur S. d'Avila Garcez (AAAI Spring Symposia, 2015)

Neural-Symbolic Learning and Reasoning: Contributions and Challenges. - 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 (AAAI Spring Symposia, 2015)

Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognition. - Tarek Richard Besold; Kai-Uwe Kühnberger; Artur S. d'Avila Garcez; Alessandro Saffiotti; Martin H. Fischer; Alan Bundy (AGI, 2015)

A hybrid recurrent neural network for music transcription. - Siddharth Sigtia; Emmanouil Benetos; Nicolas Boulanger-Lewandowski; Tillman Weyde; Artur S. d'Avila Garcez; Simon Dixon (ICASSP, 2015)

Discriminative learning and inference in the Recurrent Temporal RBM for melody modelling. - Srikanth Cherla; Son Ngoc Tran; Artur S. d'Avila Garcez; Tillman Weyde (IJCNN, 2015)

Neural-symbolic monitoring and adaptation. - Alan Perotti; Artur S. d'Avila Garcez; Guido Boella (IJCNN, 2015)

Efficient representation ranking for transfer learning. - Son Ngoc Tran; Artur S. d'Avila Garcez (IJCNN, 2015)

Hybrid Long- and Short-Term Models of Folk Melodies. - Srikanth Cherla; Son N. Tran; Tillman Weyde; Artur S. d'Avila Garcez (ISMIR, 2015)

Modelling Clinical Diagnostic Errors: A System Dynamics Approach. - Shijing Guo; Abdul V. Roudsari; Artur S. d'Avila Garcez (ITCH, 2015)

A System Dynamics Approach to Analyze Laboratory Test Errors. - Shijing Guo; Abdul V. Roudsari; Artur S. d'Avila Garcez (MIE, 2015)

Relational Knowledge Extraction from Neural Networks. - Manoel Vitor Macedo França; Artur S. d'Avila Garcez; Gerson Zaverucha (CoCo@NIPS, 2015)

Learning and Reasoning with Logic Tensor Networks. - Luciano Serafini; Artur S. d'Avila Garcez (AI*IA, 2016)

The Need for Knowledge Extraction: Understanding Harmful Gambling Behavior with Neural Networks. - Chris Percy; Artur S. d'Avila Garcez; Simo Dragicevic; Manoel V. M. França; Greg G. Slabaugh; Tillman Weyde (ECAI, 2016)

Adaptive Transferred-profile Likelihood Learning. - Son Ngoc Tran; Artur S. d'Avila Garcez (IJCNN, 2016)

Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge. - Luciano Serafini; Artur S. d'Avila Garcez (NeSy@HLAI, 2016)

A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies. - Özgür Yilmaz; Artur S. d'Avila Garcez; Daniel L. Silver (NeSy@HLAI, 2016)

Accuracy and Interpretability Trade-Offs in Machine Learning Applied to Safer Gambling. - Sanjoy Sarkar; Tillman Weyde; Artur S. d'Avila Garcez; Gregory G. Slabaugh; Simo Dragicevic; Chris Percy (CoCo@NIPS, 2016)

Generalising the Discriminative Restricted Boltzmann Machine. - Srikanth Cherla; Son N. Tran; Tillman Weyde; Artur S. d'Avila Garcez (CoRR, 2016)

Fat-Fast VG-RAM WNN: A high performance approach. - Avelino Forechi; Alberto F. De Souza; Jorcy de Oliveira Neto; Edilson de Aguiar; Claudine Badue; Artur S. d'Avila Garcez; Thiago Oliveira-Santos (Neurocomputing, 2016)

Generalising the Discriminative Restricted Boltzmann Machines. - Srikanth Cherla; Son Ngoc Tran; Artur S. d'Avila Garcez; Tillman Weyde (ICANN (2), 2017)

Extracting M of N Rules from Restricted Boltzmann Machines. - Simon Odense; Artur S. d'Avila Garcez (ICANN (2), 2017)

Logic Tensor Networks for Semantic Image Interpretation. - Ivan Donadello; Luciano Serafini; Artur S. d'Avila Garcez (IJCAI, 2017)

On the memory properties of recurrent neural models. - Arthur Jack Russell; Emmanouil Benetos; Artur S. d'Avila Garcez (IJCNN, 2017)

A Comparison between Deep Q-Networks and Deep Symbolic Reinforcement Learning. - Aimore R. R. Dutra; Artur S. d'Avila Garcez (NeSy, 2017)

Inductive Learning in Shared Neural Multi-Spaces. - Edjard de Souza Mota; Jacob M. Howe; Artur S. d'Avila Garcez (NeSy, 2017)

Confidence Values and Compact Rule Extraction From Probabilistic Neural Networks. - Simon Odense; Artur S. d'Avila Garcez (NeSy, 2017)

Category-based Inductive Learning in Shared NeMuS. - Ana Carolina Melik Schramm; Edjard de Souza Mota; Jacob M. Howe; Artur S. d'Avila Garcez (NeSy, 2017)

Learning about Actions and Events in Shared NeMuS. - Milena Rodrigues Tenorio; Edjard de Souza Mota; Jacob M. Howe; Artur S. d'Avila Garcez (NeSy, 2017)

Learning and reasoning in logic tensor networks: theory and application to semantic image interpretation. - Luciano Serafini; Ivan Donadello; Artur S. d'Avila Garcez (SAC, 2017)

The Recurrent Temporal Discriminative Restricted Boltzmann Machines. - Son N. Tran; Srikanth Cherla; Artur S. d'Avila Garcez; Tillman Weyde (CoRR, 2017)

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. - Tarek R. Besold; Artur S. d'Avila Garcez; Sebastian Bader 001; Howard Bowman; Pedro M. Domingos; Pascal Hitzler; Kai-Uwe Kühnberger; Luís C. Lamb; Daniel Lowd; Priscila Machado Vieira Lima; Leo de Penning; Gadi Pinkas; et al. (CoRR, 2017)

Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192). - Tarek R. Besold; Artur S. d'Avila Garcez; Luís C. Lamb (Dagstuhl Reports, 2017)

Reasoning in Non-probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples. - Tarek R. Besold; Artur S. d'Avila Garcez; Keith Stenning; Leendert W. N. van der Torre; Michiel van Lambalgen (Minds Mach., 2017)

Towards Symbolic Reinforcement Learning with Common Sense. - Artur S. d'Avila Garcez; Aimore Resende Riquetti Dutra; Eduardo Alonso (CoRR, 2018)

Continual Learning Augmented Investment Decisions. - Daniel Philps; Tillman Weyde; Artur S. d'Avila Garcez; Roy Batchelor (CoRR, 2018)

Speaker recognition with hybrid features from a deep belief network. - Hazrat Ali; Son Ngoc Tran; Emmanouil Benetos; Artur S. d'Avila Garcez (Neural Comput. Appl., 2018)

Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks. - Son Ngoc Tran; Artur S. d'Avila Garcez (IEEE Trans. Neural Networks Learn. Syst., 2018)

Efficient Predicate Invention using Shared NeMuS. - Edjard Mota; Jacob M. Howe; Ana Schramm; Artur S. d'Avila Garcez (NeSy@IJCAI, 2019)

Making Good on LSTMs Unfulfilled Promise. - Daniel Philps; Artur S. d'Avila Garcez; Tillman Weyde (CoRR, 2019)

Editorial. - Artur S. d'Avila Garcez; Tarek R. Besold (FLAP, 2019)

Neural-symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning. - Artur S. d'Avila Garcez; Marco Gori; Luís C. Lamb; Luciano Serafini; Michael Spranger; Son N. Tran (FLAP, 2019)

Editorial: Booming of Neural Networks and Learning Systems. - Akira Hirose 001; Alessio Micheli; Artur S. d'Avila Garcez; Choon Ki Ahn; Gang Pan 001; Hamid Reza Karimi; Jianbing Shen; José de Jesús Rubio; Lei Zhang 005; Lingjia Liu 001; Lorenzo Livi; Nian Zhang; et al. (IEEE Trans. Neural Networks Learn. Syst., 2019)

Lessons Learned from Problem Gambling Classification: Indirect Discrimination and Algorithmic Fairness. - Christian Percy; Artur S. d'Avila Garcez; Simo Dragicevic; Sanjoy Sarkar (AI4SG@AAAI Fall Symposium, 2020)

Measurable Counterfactual Local Explanations for Any Classifier. - Adam White 002; Artur S. d'Avila Garcez (ECAI, 2020)

Neural-Symbolic Relational Reasoning on Graph Models: Effective Link Inference and Computation from Knowledge Bases. - Henrique Lemos 001; Pedro H. C. Avelar; Marcelo O. R. Prates; Artur S. d'Avila Garcez; Luís C. Lamb (ICANN (1), 2020)

Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective. - Luís C. Lamb; Artur S. d'Avila Garcez; Marco Gori; Marcelo O. R. Prates; Pedro H. C. Avelar; Moshe Y. Vardi (IJCAI, 2020)

Semi-supervised GANs for Fraud Detection*. - Charitos Charitou; Artur S. d'Avila Garcez; Simo Dragicevic (IJCNN, 2020)

Neuro-Symbolic Probabilistic Argumentation Machines. - Régis Riveret; Son N. Tran; Artur S. d'Avila Garcez (KR, 2020)

A Machine Learning Approach for Colles' Fracture Treatment Diagnosis. - Kwun Ho Ngan; Artur S. d'Avila Garcez; Karen M. Knapp; Andy Appelboam; Constantino Carlos Reyes-Aldasoro (MIUA, 2020)

Layerwise Knowledge Extraction from Deep Convolutional Networks. - Simon Odense; Artur S. d'Avila Garcez (CoRR, 2020)

On the Transferability of VAE Embeddings using Relational Knowledge with Semi-Supervision. - Harald Strömfelt; Luke Dickens; Artur S. d'Avila Garcez; Alessandra Russo (CoRR, 2020)

Probabilistic approaches for music similarity using restricted Boltzmann machines. - Son N. Tran; Ngo Tung Son; Artur S. d'Avila Garcez (Neural Comput. Appl., 2020)

Sequence Classification Restricted Boltzmann Machines With Gated Units. - Son N. Tran; Artur S. d'Avila Garcez; Tillman Weyde; Jie Yin 001; Qing Zhang 001; Mohan Karunanithi (IEEE Trans. Neural Networks Learn. Syst., 2020)

Graph-Based Neural Modules to Inspect Attention-Based Architectures, A Position Paper. - Breno W. Carvalho; Artur S. d'Avila Garcez; Luís C. Lamb (TFSOCTAI@AAAI Fall Symposium, 2021)

Neural-Symbolic Integration for Fairness in AI. - Benedikt Wagner; Artur S. d'Avila Garcez (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering, 2021)

Coherent and Consistent Relational Transfer Learning with Auto-encoders. - Harald Strömfelt; Luke Dickens; Artur S. d'Avila Garcez; Alessandra Russo (NeSy, 2021)

Accountability in AI: From principles to industry-specific accreditation. - Chris Percy; Simo Dragicevic; Sanjoy Sarkar; Artur S. d'Avila Garcez (AI Commun., 2021)

Counterfactual Instances Explain Little. - Adam White 002; Artur S. d'Avila Garcez (CoRR, 2021)

Synthetic Data Generation for Fraud Detection using GANs. - Charitos Charitou; Simo Dragicevic; Artur S. d'Avila Garcez (CoRR, 2021)

Logical Boltzmann Machines. - Son N. Tran; Artur S. d'Avila Garcez (CoRR, 2021)

Neural-Symbolic Integration for Interactive Learning and Conceptual Grounding. - Benedikt Wagner; Artur S. d'Avila Garcez (CoRR, 2021)

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation. - Tarek R. Besold; Artur S. d'Avila Garcez; Sebastian Bader 001; Howard Bowman; Pedro M. Domingos; Pascal Hitzler; Kai-Uwe Kühnberger; Luís C. Lamb; Priscila Machado Vieira Lima; Leo de Penning; Gadi Pinkas; Hoifung Poon; et al. (Neuro-Symbolic Artificial Intelligence, 2021)

Logic Tensor Networks: Theory and Applications. - Luciano Serafini; Artur S. d'Avila Garcez; Samy Badreddine; Ivan Donadello; Michael Spranger; Federico Bianchi 001 (Neuro-Symbolic Artificial Intelligence, 2021)

Neural-Symbolic Reasoning Under Open-World and Closed-World Assumptions. - Benedikt Wagner; Artur S. d'Avila Garcez (AAAI Spring Symposium: MAKE, 2022)

Extracting Meaningful High-Fidelity Knowledge from Convolutional Neural Networks. - Kwun Ho Ngan; Artur S. d'Avila Garcez; Joseph Townsend (IJCNN, 2022)

Formalizing Consistency and Coherence of Representation Learning. - Harald Strömfelt; Luke Dickens; Artur S. d'Avila Garcez; Alessandra Russo (NeurIPS, 2022)

Logic Tensor Networks. - Samy Badreddine; Artur S. d'Avila Garcez; Luciano Serafini; Michael Spranger (Artif. Intell., 2022)

A Semantic Framework for Neural-Symbolic Computing. - Simon Odense; Artur d'Avila Garcez (CoRR, 2022)

Neurosymbolic Reasoning and Learning with Restricted Boltzmann Machines. - Son N. Tran; Artur S. d'Avila Garcez (AAAI, 2023)

Continual Reasoning: Non-monotonic Reasoning in Neurosymbolic AI using Continual Learning. - Sofoklis Kyriakopoulos; Artur S. d'Avila Garcez (NeSy, 2023)

Closing the Neural-Symbolic Cycle: Knowledge Extraction, User Intervention and Distillation from Convolutional Neural Networks. - Kwun Ho Ngan; James Phelan; Esma Mansouri-Benssassi; Joe Townsend; Artur S. d'Avila Garcez (NeSy, 2023)

Predicting recovery following stroke: deep learning, multimodal data and feature selection using explainable AI. - Adam White 002; Margarita Saranti; Artur S. d'Avila Garcez; Thomas M. H. Hope; Cathy J. Price; Howard Bowman (CoRR, 2023)

Modular Neural Networks for Time Series Forecasting: Interpretability and Feature Selection using Attention. - Qiqi Su; Christos Kloukinas; Artur d'Avila Garcez (CoRR, 2023)

Discovering Visual Concepts and Rules in Convolutional Neural Networks. - Joe Townsend; Esma Mansouri-Benssassi; Kwun Ho Ngan; Artur d'Avila Garcez (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Contrastive counterfactual visual explanations with overdetermination. - Adam White 002; Kwun Ho Ngan; James Phelan; Kevin Ryan; Saman Sadeghi Afgeh; Constantino Carlos Reyes-Aldasoro; Artur S. d'Avila Garcez (Mach. Learn., 2023)

Neurosymbolic AI: the 3rd wave. - Artur d'Avila Garcez; Luís C. Lamb (Artif. Intell. Rev., 2023)

Symbolic Knowledge Extraction and Distillation into Convolutional Neural Networks to Improve Medical Image Classification. - Kwun Ho Ngan; James Phelan; Joe Townsend; Artur d'Avila Garcez (IJCNN, 2024)

Hypergraph Neural Networks with Logic Clauses. - João Pedro Gandarela de Souza; Gerson Zaverucha; Artur S. d'Avila Garcez (IJCNN, 2024)

FocusLearn: Fully-Interpretable, High-Performance Modular Neural Networks for Time Series. - Qiqi Su; Christos Kloukinas; Artur d'Avila Garcez (IJCNN, 2024)

Evaluation of autonomous systems under data distribution shifts. - Daniel Sikar; Artur d'Avila Garcez (CoRR, 2024)

The Misclassification Likelihood Matrix: Some Classes Are More Likely To Be Misclassified Than Others. - Daniel Sikar; Artur d'Avila Garcez; Robin Bloomfield; Tillman Weyde; Kaleem Peeroo; Naman Singh; Maeve Hutchinson; Mirela Reljan-Delaney (CoRR, 2024)

When to Accept Automated Predictions and When to Defer to Human Judgment? - Daniel Sikar; Artur d'Avila Garcez; Tillman Weyde; Robin Bloomfield; Kaleem Peeroo (CoRR, 2024)

A semantic framework for neurosymbolic computation. - Simon Odense; Artur d'Avila Garcez (Artif. Intell., 2025)

Explorations of the Softmax Space: Knowing When the Neural Network Doesn't Know... - Daniel Sikar; Artur d'Avila Garcez; Tillman Weyde (CoRR, 2025)

Grokking Explained: A Statistical Phenomenon. - Breno W. Carvalho; Artur S. d'Avila Garcez; Luís C. Lamb; Emilio Vital Brazil (CoRR, 2025)

A Practical Tutorial on Explainable AI Techniques. - Adrien Bennetot; Ivan Donadello; Ayoub El Qadi; Mauro Dragoni; Thomas Frossard; Benedikt Wagner; Anna Saranti; Silvia Tulli; Maria Trocan; Raja Chatila 001; Andreas Holzinger; Artur d'Avila Garcez; et al. (ACM Comput. Surv., 2025)

Reasoning in Neurosymbolic AI. - Son Tran; Edjard Mota; Artur d'Avila Garcez (CoRR, 2025)

Large Language Models as Oracles for Ontology Alignment. - Sviatoslav Lushnei; Dmytro Shumskyi; Severyn Shykula; Ernesto Jiménez-Ruiz; Artur d'Avila Garcez (CoRR, 2025)