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Learning Relational Representations with Auto-encoding Logic Programs

Learning Relational Representations with Auto-encoding Logic Programs

29 March 2019
Sebastijan Dumancic
Tias Guns
Wannes Meert
Hendrik Blockeel
    NAI
ArXivPDFHTML

Papers citing "Learning Relational Representations with Auto-encoding Logic Programs"

17 / 17 papers shown
Title
Scalable Knowledge Refactoring using Constrained Optimisation
Scalable Knowledge Refactoring using Constrained Optimisation
Minghao Liu
David M. Cerna
Filipe Gouveia
Andrew Cropper
25
0
0
21 Aug 2024
Learning big logical rules by joining small rules
Learning big logical rules by joining small rules
Céline Hocquette
Andreas Niskanen
Rolf Morel
Matti Jarvisalo
Andrew Cropper
29
1
0
29 Jan 2024
Learning logic programs by discovering higher-order abstractions
Learning logic programs by discovering higher-order abstractions
Céline Hocquette
Sebastijan Dumancic
Andrew Cropper
19
2
0
16 Aug 2023
Learning logic programs by combining programs
Learning logic programs by combining programs
Andrew Cropper
Céline Hocquette
AI4CE
24
7
0
01 Jun 2022
Learning logic programs by discovering where not to search
Learning logic programs by discovering where not to search
Andrew Cropper
Céline Hocquette
LRM
19
0
0
20 Feb 2022
From Statistical Relational to Neurosymbolic Artificial Intelligence: a
  Survey
From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey
Giuseppe Marra
Sebastijan Dumancic
Robin Manhaeve
Luc de Raedt
NAI
23
60
0
25 Aug 2021
Predicate Invention by Learning From Failures
Predicate Invention by Learning From Failures
Andrew Cropper
Rolf Morel
19
12
0
29 Apr 2021
Inductive logic programming at 30
Inductive logic programming at 30
Andrew Cropper
Sebastijan Dumancic
Richard Evans
Stephen Muggleton
AI4CE
33
75
0
21 Feb 2021
A Study of Continuous Vector Representationsfor Theorem Proving
A Study of Continuous Vector Representationsfor Theorem Proving
Stanislaw J. Purgal
Julian Parsert
C. Kaliszyk
NAI
11
5
0
22 Jan 2021
Top Program Construction and Reduction for polynomial time
  Meta-Interpretive Learning
Top Program Construction and Reduction for polynomial time Meta-Interpretive Learning
S. Patsantzis
Stephen Muggleton
30
5
0
13 Jan 2021
Propositionalization and Embeddings: Two Sides of the Same Coin
Propositionalization and Embeddings: Two Sides of the Same Coin
Nada Lavrac
Blaž Škrlj
Marko Robnik-Šikonja
10
26
0
08 Jun 2020
Learning programs by learning from failures
Learning programs by learning from failures
Andrew Cropper
Rolf Morel
29
87
0
05 May 2020
Knowledge Refactoring for Inductive Program Synthesis
Knowledge Refactoring for Inductive Program Synthesis
Sebastijan Dumancic
Tias Guns
Andrew Cropper
6
2
0
21 Apr 2020
Turning 30: New Ideas in Inductive Logic Programming
Turning 30: New Ideas in Inductive Logic Programming
Andrew Cropper
Sebastijan Dumancic
Stephen Muggleton
LRM
AI4CE
14
83
0
25 Feb 2020
Relational Neural Machines
Relational Neural Machines
G. Marra
Michelangelo Diligenti
Francesco Giannini
Marco Gori
Marco Maggini
NAI
BDL
25
38
0
06 Feb 2020
Forgetting to learn logic programs
Forgetting to learn logic programs
Andrew Cropper
CLL
21
16
0
15 Nov 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
30
542
0
18 Jul 2019
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