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A Sound and Complete Algorithm for Learning Causal Models from
  Relational Data

A Sound and Complete Algorithm for Learning Causal Models from Relational Data

26 September 2013
Marc E. Maier
Katerina Marazopoulou
David Arbour
David D. Jensen
    CML
ArXiv (abs)PDFHTML

Papers citing "A Sound and Complete Algorithm for Learning Causal Models from Relational Data"

15 / 15 papers shown
Title
Compositional Models for Estimating Causal Effects
Compositional Models for Estimating Causal Effects
Purva Pruthi
David D. Jensen
CML
225
0
0
25 Jun 2024
Lifted Causal Inference in Relational Domains
Lifted Causal Inference in Relational Domains
Malte Luttermann
Mattis Hartwig
Tanya Braun
Ralf Möller
Marcel Gehrke
62
5
0
15 Mar 2024
Directed Acyclic Graph Structure Learning from Dynamic Graphs
Directed Acyclic Graph Structure Learning from Dynamic Graphs
Shaohua Fan
Shuyang Zhang
Xiao Wang
Chuan Shi
CML
130
5
0
30 Nov 2022
Learning Relational Causal Models with Cycles through Relational
  Acyclification
Learning Relational Causal Models with Cycles through Relational Acyclification
Ragib Ahsan
David Arbour
Elena Zheleva
111
2
0
25 Aug 2022
Non-Parametric Inference of Relational Dependence
Non-Parametric Inference of Relational Dependence
Ragib Ahsan
Zahra Fatemi
David Arbour
Elena Zheleva
107
1
0
30 Jun 2022
Relational Causal Models with Cycles:Representation and Reasoning
Relational Causal Models with Cycles:Representation and Reasoning
Ragib Ahsan
David Arbour
Elena Zheleva
LRM
46
4
0
22 Feb 2022
Minimizing Interference and Selection Bias in Network Experiment Design
Minimizing Interference and Selection Bias in Network Experiment Design
Zahra Fatemi
Elena Zheleva
CML
31
20
0
15 Apr 2020
Causal Relational Learning
Causal Relational Learning
Babak Salimi
Harsh Parikh
Moe Kayali
Sudeepa Roy
Lise Getoor
Dan Suciu
CML
52
44
0
07 Apr 2020
Towards Robust Relational Causal Discovery
Towards Robust Relational Causal Discovery
Sanghack Lee
Vasant Honavar
78
9
0
05 Dec 2019
Causal Inference Under Interference And Network Uncertainty
Causal Inference Under Interference And Network Uncertainty
Rohit Bhattacharya
Daniel Malinsky
I. Shpitser
CML
64
64
0
29 Jun 2019
What do we need to build explainable AI systems for the medical domain?
What do we need to build explainable AI systems for the medical domain?
Andreas Holzinger
Chris Biemann
C. Pattichis
D. Kell
91
694
0
28 Dec 2017
A Framework for Inferring Causality from Multi-Relational Observational
  Data using Conditional Independence
A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence
Sudeepa Roy
Babak Salimi
CMLAI4CE
35
0
0
08 Aug 2017
Lifted Representation of Relational Causal Models Revisited:
  Implications for Reasoning and Structure Learning
Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning
Sanghack Lee
Vasant Honavar
41
6
0
10 Aug 2015
Reasoning about Independence in Probabilistic Models of Relational Data
Reasoning about Independence in Probabilistic Models of Relational Data
Marc E. Maier
Katerina Marazopoulou
David D. Jensen
81
34
0
18 Feb 2013
Lifted Graphical Models: A Survey
Lifted Graphical Models: A Survey
Lilyana Mihalkova
Lise Getoor
3DV
167
96
0
25 Jul 2011
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