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Logic Tensor Networks for Semantic Image Interpretation

Logic Tensor Networks for Semantic Image Interpretation

24 May 2017
Ivan Donadello
Luciano Serafini
Artur Garcez
ArXiv (abs)PDFHTML

Papers citing "Logic Tensor Networks for Semantic Image Interpretation"

40 / 90 papers shown
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge
  Graphs
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge GraphsExtended Semantic Web Conference (ESWC), 2021
Yushan Liu
Marcel Hildebrandt
Mitchell Joblin
Martin Ringsquandl
Rime Raissouni
Volker Tresp
167
48
0
18 Mar 2021
Modular Design Patterns for Hybrid Learning and Reasoning Systems: a
  taxonomy, patterns and use cases
Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases
M. V. Bekkum
M. D. Boer
F. V. Harmelen
André Meyer-Vitali
A. T. Teije
202
98
0
23 Feb 2021
Logic Tensor Networks
Logic Tensor NetworksArtificial Intelligence (AI), 2020
Samy Badreddine
Artur Garcez
Luciano Serafini
Michael Spranger
NAI
677
275
0
25 Dec 2020
Neurosymbolic AI: The 3rd Wave
Neurosymbolic AI: The 3rd WaveArtificial Intelligence Review (AIR), 2020
Artur Garcez
Luís C. Lamb
NAI
370
422
0
10 Dec 2020
Zero-Shot Learning with Knowledge Enhanced Visual Semantic Embeddings
Zero-Shot Learning with Knowledge Enhanced Visual Semantic Embeddings
Karan Sikka
Jihua Huang
Andrew Silberfarb
Prateeth Nayak
Luke Rohrer
Pritish Sahu
John Byrnes
Ajay Divakaran
R. Rohwer
166
4
0
21 Nov 2020
Exploring End-to-End Differentiable Natural Logic Modeling
Exploring End-to-End Differentiable Natural Logic Modeling
Yufei Feng
Zióu Zheng
Quan Liu
Michael A. Greenspan
Xiao-Dan Zhu
194
15
0
08 Nov 2020
Neural-Symbolic Integration: A Compositional Perspective
Neural-Symbolic Integration: A Compositional Perspective
Efthymia Tsamoura
Loizos Michael
NAI
209
80
0
22 Oct 2020
Modeling Content and Context with Deep Relational Learning
Modeling Content and Context with Deep Relational LearningTransactions of the Association for Computational Linguistics (TACL), 2020
Maria Leonor Pacheco
Dan Goldwasser
NAI
256
35
0
20 Oct 2020
Abductive Knowledge Induction From Raw Data
Abductive Knowledge Induction From Raw Data
Wang-Zhou Dai
Stephen Muggleton
295
58
0
07 Oct 2020
Extending Answer Set Programs with Neural Networks
Extending Answer Set Programs with Neural Networks
Zhun Yang
ReLMNAILRM
214
0
0
22 Sep 2020
Zero-shot Multi-Domain Dialog State Tracking Using Descriptive Rules
Zero-shot Multi-Domain Dialog State Tracking Using Descriptive RulesInternational Workshop on Neural-Symbolic Learning and Reasoning (NeSy), 2020
Edgar Altszyler
Pablo Brusco
Nikoletta Basiou
John Byrnes
D. Vergyri
261
7
0
17 Sep 2020
Neural Networks Enhancement with Logical Knowledge
Neural Networks Enhancement with Logical Knowledge
Alessandro Daniele
Luciano Serafini
NAI
214
5
0
13 Sep 2020
Efficient Generation of Structured Objects with Constrained Adversarial
  Networks
Efficient Generation of Structured Objects with Constrained Adversarial NetworksNeural Information Processing Systems (NeurIPS), 2020
Luca Di Liello
Pierfrancesco Ardino
Jacopo Gobbi
Paolo Morettin
Stefano Teso
Baptiste Caramiaux
GAN
202
39
0
26 Jul 2020
Learning Reasoning Strategies in End-to-End Differentiable Proving
Learning Reasoning Strategies in End-to-End Differentiable ProvingInternational Conference on Machine Learning (ICML), 2020
Pasquale Minervini
Sebastian Riedel
Pontus Stenetorp
Edward Grefenstette
Tim Rocktaschel
LRM
363
99
0
13 Jul 2020
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label
  Classifiers
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers
S. Melacci
Gabriele Ciravegna
Angelo Sotgiu
Ambra Demontis
Battista Biggio
Marco Gori
Fabio Roli
302
21
0
06 Jun 2020
Analyzing Differentiable Fuzzy Implications
Analyzing Differentiable Fuzzy Implications
Emile van Krieken
Erman Acar
F. V. Harmelen
AI4CE
125
30
0
04 Jun 2020
Randomly Weighted, Untrained Neural Tensor Networks Achieve Greater
  Relational Expressiveness
Randomly Weighted, Untrained Neural Tensor Networks Achieve Greater Relational Expressiveness
Jinyung Hong
Theodore P. Pavlic
233
0
0
01 Jun 2020
Knowledge Graph Embeddings and Explainable AI
Knowledge Graph Embeddings and Explainable AI
Federico Bianchi
Gaetano Rossiello
Luca Costabello
M. Palmonari
Pasquale Minervini
219
87
0
30 Apr 2020
From Statistical Relational to Neuro-Symbolic Artificial Intelligence
From Statistical Relational to Neuro-Symbolic Artificial IntelligenceInternational Joint Conference on Artificial Intelligence (IJCAI), 2020
Luc de Raedt
Sebastijan Dumancic
Robin Manhaeve
Giuseppe Marra
NAI
220
127
0
18 Mar 2020
Analyzing Differentiable Fuzzy Logic Operators
Analyzing Differentiable Fuzzy Logic OperatorsArtificial Intelligence (AIJ), 2020
Emile van Krieken
Erman Acar
F. V. Harmelen
NAIAI4CE
386
161
0
14 Feb 2020
Relational Neural Machines
Relational Neural MachinesEuropean Conference on Artificial Intelligence (ECAI), 2020
G. Marra
Michelangelo Diligenti
Francesco Giannini
Marco Gori
Marco Maggini
NAIBDL
279
41
0
06 Feb 2020
A New Approach for Explainable Multiple Organ Annotation with Few Data
A New Approach for Explainable Multiple Organ Annotation with Few DataInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Régis Pierrard
Jean-Philippe Poli
C´eline Hudelot
109
8
0
30 Dec 2019
From Shallow to Deep Interactions Between Knowledge Representation,
  Reasoning and Machine Learning (Kay R. Amel group)
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group)
Zied Bouraoui
Antoine Cornuéjols
Thierry Denoeux
Sebastien Destercke
Didier Dubois
...
Jérôme Mengin
H. Prade
Steven Schockaert
M. Serrurier
Christel Vrain
305
14
0
13 Dec 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies,
  Opportunities and Challenges toward Responsible AI
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIInformation Fusion (Inf. Fusion), 2019
Alejandro Barredo Arrieta
Natalia Díaz Rodríguez
Javier Del Ser
Adrien Bennetot
Siham Tabik
...
S. Gil-Lopez
Daniel Molina
Richard Benjamins
Raja Chatila
Francisco Herrera
XAI
994
7,655
0
22 Oct 2019
Compensating Supervision Incompleteness with Prior Knowledge in Semantic
  Image Interpretation
Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image InterpretationIEEE International Joint Conference on Neural Network (IJCNN), 2019
Ivan Donadello
Luciano Serafini
161
26
0
01 Oct 2019
Towards Explainable Neural-Symbolic Visual Reasoning
Towards Explainable Neural-Symbolic Visual Reasoning
Adrien Bennetot
J. Laurent
Raja Chatila
Natalia Díaz Rodríguez
XAI
133
1
0
19 Sep 2019
Strong Equivalence for LPMLN Programs
Strong Equivalence for LPMLN Programs
Joohyung Lee
Man Luo
97
3
0
18 Sep 2019
Semi-Supervised Learning using Differentiable Reasoning
Semi-Supervised Learning using Differentiable Reasoning
Emile van Krieken
Erman Acar
F. V. Harmelen
DRL
167
22
0
13 Aug 2019
T-Norms Driven Loss Functions for Machine Learning
T-Norms Driven Loss Functions for Machine Learning
G. Marra
Francesco Giannini
Michelangelo Diligenti
Marco Maggini
Marco Gori
422
16
0
26 Jul 2019
Neural Probabilistic Logic Programming in DeepProbLog
Neural Probabilistic Logic Programming in DeepProbLog
Robin Manhaeve
Sebastijan Dumancic
Angelika Kimmig
T. Demeester
Luc de Raedt
NAI
417
666
0
18 Jul 2019
On the relation between Loss Functions and T-Norms
On the relation between Loss Functions and T-NormsInternational Conference on Inductive Logic Programming (ILP), 2019
Francesco Giannini
G. Marra
Michelangelo Diligenti
Marco Maggini
Marco Gori
90
10
0
18 Jul 2019
Self-organized inductive reasoning with NeMuS
Self-organized inductive reasoning with NeMuS
L. Barreto
E. Mota
NAILRM
66
2
0
16 Jun 2019
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
F. V. Harmelen
A. T. Teije
181
80
0
29 May 2019
Neural-Symbolic Computing: An Effective Methodology for Principled
  Integration of Machine Learning and Reasoning
Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning
Artur Garcez
Marco Gori
Luís C. Lamb
Luciano Serafini
Michael Spranger
Son N. Tran
NAI
245
350
0
15 May 2019
Integrating Learning and Reasoning with Deep Logic Models
Integrating Learning and Reasoning with Deep Logic Models
G. Marra
Francesco Giannini
Michelangelo Diligenti
Marco Gori
NAI
185
60
0
14 Jan 2019
Reasoning over RDF Knowledge Bases using Deep Learning
Reasoning over RDF Knowledge Bases using Deep Learning
Monireh Ebrahimi
Md Kamruzzaman Sarker
Federico Bianchi
Ning Xie
Derek Doran
Pascal Hitzler
ReLMLRM
159
20
0
09 Nov 2018
Logical Rule Induction and Theory Learning Using Neural Theorem Proving
Logical Rule Induction and Theory Learning Using Neural Theorem Proving
Andres Campero
A. Pareja
Tim Klinger
J. Tenenbaum
Sebastian Riedel
NAIAI4CE
292
42
0
06 Sep 2018
Ontology Reasoning with Deep Neural Networks
Ontology Reasoning with Deep Neural Networks
Patrick Hohenecker
Thomas Lukasiewicz
NAI
275
104
0
24 Aug 2018
Towards Symbolic Reinforcement Learning with Common Sense
Towards Symbolic Reinforcement Learning with Common Sense
Artur Garcez
Aimore Dutra
E. Alonso
OffRL
122
31
0
23 Apr 2018
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
A Semantic Loss Function for Deep Learning with Symbolic Knowledge
Aoxiang Fan
Zilu Zhang
Tal Friedman
Yitao Liang
Karen Ullrich
381
503
0
29 Nov 2017
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