Artur S. d'Avila Garcez

According to our database1, Artur S. d'Avila Garcez authored at least 105 papers between 1997 and 2019.

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2019
Editorial: Booming of Neural Networks and Learning Systems.
IEEE Trans. Neural Netw. Learning Syst., 2019

Neural-symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning.
FLAP, 2019

Editorial.
FLAP, 2019

2018
Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks.
IEEE Trans. Neural Netw. Learning Syst., 2018

Speaker recognition with hybrid features from a deep belief network.
Neural Computing and Applications, 2018

2017
Reasoning in Non-probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples.
Minds and Machines, 2017

Human-Like Neural-Symbolic Computing (Dagstuhl Seminar 17192).
Dagstuhl Reports, 2017

Learning and reasoning in logic tensor networks: theory and application to semantic image interpretation.
Proceedings of the Symposium on Applied Computing, 2017

Learning about Actions and Events in Shared NeMuS.
Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017

Category-based Inductive Learning in Shared NeMuS.
Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017

Confidence Values and Compact Rule Extraction From Probabilistic Neural Networks.
Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017

Inductive Learning in Shared Neural Multi-Spaces.
Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017

A Comparison between Deep Q-Networks and Deep Symbolic Reinforcement Learning.
Proceedings of the Twelfth International Workshop on Neural-Symbolic Learning and Reasoning, 2017

On the memory properties of recurrent neural models.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Logic Tensor Networks for Semantic Image Interpretation.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Extracting M of N Rules from Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

Generalising the Discriminative Restricted Boltzmann Machines.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

2016
Fat-Fast VG-RAM WNN: A high performance approach.
Neurocomputing, 2016

Accuracy and Interpretability Trade-Offs in Machine Learning Applied to Safer Gambling.
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), 2016

A Proposal for Common Dataset in Neural-Symbolic Reasoning Studies.
Proceedings of the 11th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'16) co-located with the Joint Multi-Conference on Human-Level Artificial Intelligence (HLAI 2016), 2016

Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge.
Proceedings of the 11th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'16) co-located with the Joint Multi-Conference on Human-Level Artificial Intelligence (HLAI 2016), 2016

Adaptive Transferred-profile Likelihood Learning.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

The Need for Knowledge Extraction: Understanding Harmful Gambling Behavior with Neural Networks.
Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016

Learning and Reasoning with Logic Tensor Networks.
Proceedings of the AI*IA 2016: Advances in Artificial Intelligence - XVth International Conference of the Italian Association for Artificial Intelligence, Genova, Italy, November 29, 2016

2015
Runtime Verification Through Forward Chaining.
Proceedings of the Runtime Verification - 6th International Conference, 2015

Relational Knowledge Extraction from Neural Networks.
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), 2015

A System Dynamics Approach to Analyze Laboratory Test Errors.
Proceedings of the Digital Healthcare Empowering Europeans, 2015

Modelling Clinical Diagnostic Errors: A System Dynamics Approach.
Proceedings of the Driving Quality in Informatics: Fulfilling the Promise, 2015

Hybrid Long- and Short-Term Models of Folk Melodies.
Proceedings of the 16th International Society for Music Information Retrieval Conference, 2015

Efficient representation ranking for transfer learning.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Neural-symbolic monitoring and adaptation.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Discriminative learning and inference in the Recurrent Temporal RBM for melody modelling.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

A hybrid recurrent neural network for music transcription.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Anchoring Knowledge in Interaction: Towards a Harmonic Subsymbolic/Symbolic Framework and Architecture of Computational Cognition.
Proceedings of the Artificial General Intelligence, 2015

Neural-Symbolic Learning and Reasoning: Contributions and Challenges.
Proceedings of the 2015 AAAI Spring Symposia, 2015

Neural Relational Learning Through Semi-Propositionalization of Bottom Clauses.
Proceedings of the 2015 AAAI Spring Symposia, 2015

2014
Fast relational learning using bottom clause propositionalization with artificial neural networks.
Machine Learning, 2014

A neural cognitive model of argumentation with application to legal inference and decision making.
J. Applied Logic, 2014

Neural-Symbolic Learning and Reasoning (Dagstuhl Seminar 14381).
Dagstuhl Reports, 2014

Runtime Verification Through Forward Chaining.
Proceedings of the Proceedings First Workshop on Horn Clauses for Verification and Synthesis, 2014

Scalable Process Monitoring through Rules and Neural Networks.
Proceedings of the 4th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2014), 2014

Feature Preprocessing with Restricted Boltzmann Machines for Music Similarity Learning.
Proceedings of the AES International Conference on Semantic Audio 2014, 2014

A Causal Loop Approach to the Study of Diagnostic Errors.
Proceedings of the e-Health - For Continuity of Care - Proceedings of MIE2014, the 25th European Medical Informatics Conference, Istanbul, Turkey, August 31, 2014

An RNN-based Music Language Model for Improving Automatic Music Transcription.
Proceedings of the 15th International Society for Music Information Retrieval Conference, 2014

Multiple Viewpiont Melodic Prediction with Fixed-Context Neural Networks.
Proceedings of the 15th International Society for Music Information Retrieval Conference, 2014

Learning motion-difference features using Gaussian restricted Boltzmann machines for efficient human action recognition.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Neural Networks for Runtime Verification.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Applying Neural-Symbolic Cognitive Agents in Intelligent Transport Systems to reduce CO2 emissions.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Low-Cost Representation for Restricted Boltzmann Machines.
Proceedings of the Neural Information Processing - 21st International Conference, 2014

Neural-symbolic cognitive agents: architecture, theory and application.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

2013
A Distributed Model For Multiple-Viewpoint Melodic Prediction.
Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013

Dreaming Machines: On multimodal fusion and information retrieval using neural-symbolic cognitive agents.
Proceedings of the 2013 Imperial College Computing Student Workshop, 2013

Relational Knowledge Extraction from Attribute-Value Learners.
Proceedings of the 2013 Imperial College Computing Student Workshop, 2013

2012
Reports of the AAAI 2012 Conference Workshops.
AI Magazine, 2012

Multi-instance learning using recurrent neural networks.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Learning and reasoning about norms using neural-symbolic systems.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

2011
Learning and Representing Temporal Knowledge in Recurrent Networks.
IEEE Trans. Neural Networks, 2011

Embedding Normative Reasoning into Neural Symbolic Systems.
Proceedings of the Seventh International Workshop on Neural-Symbolic Learning and Reasoning, 2011

A Neural-Symbolic Cognitive Agent for Online Learning and Reasoning.
Proceedings of the IJCAI 2011, 2011

Learning to adapt requirements specifications of evolving systems.
Proceedings of the 33rd International Conference on Software Engineering, 2011

Neural-Symbolic Cognitive Agents: Architecture and Theory.
Proceedings of the 2011 Imperial College Computing Student Workshop, 2011

Neural symbolic architecture for normative agents.
Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), 2011

2010
Reports of the AAAI 2010 Conference Workshops.
AI Magazine, 2010

Integrating model verification and self-adaptation.
Proceedings of the ASE 2010, 2010

SOAR - Sparse Oracle-based Adaptive Rule extraction: Knowledge extraction from large-scale datasets to detect credit card fraud.
Proceedings of the International Joint Conference on Neural Networks, 2010

First-order logic learning in Artificial Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2010

Neuro-symbolic Representation of Logic Programs Defining Infinite Sets.
Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

Representing, Learning and Extracting Temporal Knowledge from Neural Networks: A Case Study.
Proceedings of the Artificial Neural Networks, 2010

Neurons and Symbols: A Manifesto.
Proceedings of the Learning paradigms in dynamic environments, 25.07. - 30.07.2010, 2010

2009
Neural-Symbolic Cognitive Reasoning
Cognitive Technologies, Springer, ISBN: 978-3-540-73245-7, 2009

Logical Modes of Attack in Argumentation Networks.
Studia Logica, 2009

Preface: Reinforcement Learning.
J. Algorithms, 2009

2008
Symbolic Knowledge Extraction from Support Vector Machines: A Geometric Approach.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

2007
Advances in Neural-Symbolic Learning Systems: Modal and Temporal Reasoning.
Proceedings of the Perspectives of Neural-Symbolic Integration, 2007

Connectionist modal logic: Representing modalities in neural networks.
Theor. Comput. Sci., 2007

Reasoning and Learning About Past Temporal Knowledge in Connectionist Models.
Proceedings of the International Joint Conference on Neural Networks, 2007

Editorial.
Proceedings of the 3rd International Workshop on Neural-Symbolic Learning and Reasoning, 2007

Towards Reasoning about the Past in Neural-symbolic Systems.
Proceedings of the 3rd International Workshop on Neural-Symbolic Learning and Reasoning, 2007

A Connectionist Cognitive Model for Temporal Synchronisation and Learning.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Connectionist computations of intuitionistic reasoning.
Theor. Comput. Sci., 2006

A Connectionist Computational Model for Epistemic and Temporal Reasoning.
Neural Computation, 2006

Improving VG-RAM Neural Networks Performance Using Knowledge Correlation.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Combining Architectures for Temporal Learning in Neural-Symbolic Systems.
Proceedings of the 6th International Conference on Hybrid Intelligent Systems (HIS 2006), 2006

2005
Value-based Argumentation Frameworks as Neural-symbolic Learning Systems.
J. Log. Comput., 2005

A Connectionist Model for Constructive Modal Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Computing First-Order Logic Programs by Fibring Artificial Neural Networks.
Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, 2005

Fewer Epistemological Challenges for Connectionism.
Proceedings of the New Computational Paradigms, 2005

Neural-Symbolic Systems and the Case for Non-Classical Reasoning.
Proceedings of the We Will Show Them! Essays in Honour of Dov Gabbay, Volume One, 2005

2004
Journal of Applied Logic Special Volume on Neural-Symbolic Systems.
J. Applied Logic, 2004

Applying connectionist modal logics to distributed knowledge representation problems.
International Journal on Artificial Intelligence Tools, 2004

Reasoning About Requirements Evolution Using Clustered Belief Revision.
Proceedings of the Advances in Artificial Intelligence - SBIA 2004, 17th Brazilian Symposium on Artificial Intelligence, São Luis, Maranhão, Brazil, September 29, 2004

Argumentation Neural Networks.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

Towards a Connectionist Argumentation Framework.
Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

Fibring Neural Networks.
Proceedings of the Nineteenth National Conference on Artificial Intelligence, 2004

2003
Combining abductive reasoning and inductive learning to evolve requirements specifications.
IEE Proceedings - Software, 2003

Revising Rules to Capture Requirements Traceability Relations: A Machine Learning Approach.
Proceedings of the Fifteenth International Conference on Software Engineering & Knowledge Engineering (SEKE'2003), 2003

Reasoning about Time and Knowledge in Neural Symbolic Learning Systems.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Neural-Symbolic Intuitionistic Reasoning.
Proceedings of the Design and Application of Hybrid Intelligent Systems, 2003

Distributed Knowledge Representation in Neural-Symbolic Learning Systems: A Case Study.
Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference, 2003

2002
Neural-symbolic learning systems - foundations and applications.
Perspectives in neural computing, Springer, ISBN: 978-1-85233-512-0, 2002

2001
Symbolic knowledge extraction from trained neural networks: A sound approach.
Artif. Intell., 2001

An Analysis-Revision Cycle to Evolve Requirements Specifications.
Proceedings of the 16th IEEE International Conference on Automated Software Engineering (ASE 2001), 2001

1999
The Connectionist Inductive Learning and Logic Programming System.
Appl. Intell., 1999

1998
Inducing Relational Concepts with Neural Networks via the LINUS System.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

1997
Applying the connectionist inductive learning and logic programming system to power system diagnosis.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997


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