Artur d'Avila Garcez
Artur d'Avila Garcez
Professor of Computer Science. City, University of London
Verified email at - Homepage
Cited by
Cited by
Neural-symbolic learning systems
AS d’Avila Garcez, LC Lamb, DM Gabbay
Neural-Symbolic Cognitive Reasoning, 35-54, 2009
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
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
Neural-symbolic cognitive reasoning
AS D'Avila Garcez, LC Lamb, DM Gabbay
Neural-Symbolic Cognitive Reasoning:, Cognitive Technologies, Volume. ISBNá…, 2009
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
Logic tensor networks: Deep learning and logical reasoning from data and knowledge
L Serafini, AA Garcez
arXiv preprint arXiv:1606.04422, 2016
Neurosymbolic AI: the 3rd wave
AA Garcez, LC Lamb
Artificial Intelligence Review 56 (11), 12387-12406, 2023
Logic tensor networks for semantic image interpretation
I Donadello, L Serafini, ADA Garcez
arXiv preprint arXiv:1705.08968, 2017
The Connectionist Inductive Learning and Logic Programming System
AG AS, G Zaverucha
Applied Intelligence 11 (1), 59-77, 1999
Neural-symbolic learning and reasoning: contributions and challenges
AA Garcez, TR Besold, L De Raedt, P F÷ldiak, P Hitzler, T Icard, ...
2015 AAAI Spring Symposium Series, 2015
Logic tensor networks
S Badreddine, AA Garcez, L Serafini, M Spranger
Artificial Intelligence 303, 103649, 2022
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
Fast relational learning using bottom clause propositionalization with artificial neural networks
MVM Franša, G Zaverucha, AS d’Avila Garcez
Machine learning 94, 81-104, 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
Measurable counterfactual local explanations for any classifier
A White, A d’Avila Garcez
ECAI 2020, 2529-2535, 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
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
Predicting online gambling self-exclusion: An analysis of the performance of supervised machine learning models
C Percy, M Franša, S Dragičević, A d’Avila Garcez
International Gambling Studies 16 (2), 193-210, 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
Connectionist modal logic: Representing modalities in neural networks
AS d’Avila Garcez, LC Lamb, DM Gabbay
Theoretical Computer Science 371 (1), 34-53, 2007
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