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Semi-Supervised Learning using Differentiable Reasoning

Semi-Supervised Learning using Differentiable Reasoning

13 August 2019
Emile van Krieken
Erman Acar
F. V. Harmelen
    DRL
ArXiv (abs)PDFHTML

Papers citing "Semi-Supervised Learning using Differentiable Reasoning"

15 / 15 papers shown
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic
  Segmentation
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic SegmentationIEEE International Conference on Computer Vision (ICCV), 2023
Chen Liang
Wenguan Wang
Jiaxu Miao
Yi Yang
NAI
250
55
0
24 Aug 2023
logLTN: Differentiable Fuzzy Logic in the Logarithm Space
logLTN: Differentiable Fuzzy Logic in the Logarithm Space
Samy Badreddine
Luciano Serafini
Michael Spranger
199
2
0
26 Jun 2023
Transfer Learning with Synthetic Corpora for Spatial Role Labeling and
  Reasoning
Transfer Learning with Synthetic Corpora for Spatial Role Labeling and ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Roshanak Mirzaee
Parisa Kordjamshidi
SyDaLRM
238
43
0
30 Oct 2022
Scalable Regularization of Scene Graph Generation Models using Symbolic
  Theories
Scalable Regularization of Scene Graph Generation Models using Symbolic Theories
Davide Buffelli
Efthymia Tsamoura
238
2
0
06 Sep 2022
Knowledge Enhanced Neural Networks for relational domains
Knowledge Enhanced Neural Networks for relational domainsInternational Conference of the Italian Association for Artificial Intelligence (AIxIA), 2022
Alessandro Daniele
Luciano Serafini
241
11
0
31 May 2022
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep
  learning representations with expert knowledge graphs: the MonuMAI cultural
  heritage use case
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use caseInformation Fusion (Inf. Fusion), 2021
Natalia Díaz Rodríguez
Alberto Lamas
Jules Sanchez
Gianni Franchi
Ivan Donadello
Siham Tabik
David Filliat
P. Cruz
Rosana Montes
Francisco Herrera
350
98
0
24 Apr 2021
Logic Tensor Networks
Logic Tensor NetworksArtificial Intelligence (AI), 2020
Samy Badreddine
Artur Garcez
Luciano Serafini
Michael Spranger
NAI
760
310
0
25 Dec 2020
Neural-Symbolic Integration: A Compositional Perspective
Neural-Symbolic Integration: A Compositional Perspective
Efthymia Tsamoura
Loizos Michael
NAI
306
83
0
22 Oct 2020
Neural Networks Enhancement with Logical Knowledge
Neural Networks Enhancement with Logical Knowledge
Alessandro Daniele
Luciano Serafini
NAI
258
6
0
13 Sep 2020
A Probabilistic Model for Discriminative and Neuro-Symbolic
  Semi-Supervised Learning
A Probabilistic Model for Discriminative and Neuro-Symbolic Semi-Supervised Learning
Carl Allen
Ivana Balavzević
Timothy M. Hospedales
BDL
321
1
0
10 Jun 2020
Analyzing Differentiable Fuzzy Implications
Analyzing Differentiable Fuzzy Implications
Emile van Krieken
Erman Acar
F. V. Harmelen
AI4CE
209
30
0
04 Jun 2020
Teaching the Old Dog New Tricks: Supervised Learning with Constraints
Teaching the Old Dog New Tricks: Supervised Learning with Constraints
F. Detassis
M. Lombardi
M. Milano
201
29
0
25 Feb 2020
Injecting Domain Knowledge in Neural Networks: a Controlled Experiment
  on a Constrained Problem
Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem
Mattia Silvestri
M. Lombardi
M. Milano
AI4CE
290
22
0
25 Feb 2020
Analyzing Differentiable Fuzzy Logic Operators
Analyzing Differentiable Fuzzy Logic OperatorsArtificial Intelligence (AIJ), 2020
Emile van Krieken
Erman Acar
F. V. Harmelen
NAIAI4CE
519
165
0
14 Feb 2020
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
521
16
0
26 Jul 2019
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