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Bayes-Ball: The Rational Pastime (for Determining Irrelevance and
  Requisite Information in Belief Networks and Influence Diagrams)

Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)

30 January 2013
Ross D. Shachter
ArXiv (abs)PDFHTML

Papers citing "Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)"

36 / 36 papers shown
Title
Linear-Time Primitives for Algorithm Development in Graphical Causal Inference
Linear-Time Primitives for Algorithm Development in Graphical Causal Inference
Marcel Wienöbst
Sebastian Weichwald
Leonard Henckel
17
0
0
18 Jun 2025
A Graphical Approach to State Variable Selection in Off-policy Learning
Joakim Blach Andersen
Qingyuan Zhao
CMLOffRL
72
0
0
03 Jan 2025
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning
Emile Anand
Ishani Karmarkar
Guannan Qu
179
2
0
01 Dec 2024
Estimating Causal Effects in Partially Directed Parametric Causal Factor
  Graphs
Estimating Causal Effects in Partially Directed Parametric Causal Factor Graphs
Malte Luttermann
Tanya Braun
Ralf Möller
Marcel Gehrke
106
2
0
11 Nov 2024
Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies
Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies
H. Jeong
Adiba Ejaz
Jin Tian
Elias Bareinboim
58
2
0
22 Sep 2024
Mechanisms for Data Sharing in Collaborative Causal Inference (Extended
  Version)
Mechanisms for Data Sharing in Collaborative Causal Inference (Extended Version)
Björn Filter
Ralf Möller
Özgür L. Özçep
FedML
58
0
0
04 Jul 2024
Adjustment Identification Distance: A gadjid for Causal Structure
  Learning
Adjustment Identification Distance: A gadjid for Causal Structure Learning
Leonard Henckel
Theo Würtzen
Sebastian Weichwald
CML
105
11
0
13 Feb 2024
Stabilizing Subject Transfer in EEG Classification with Divergence
  Estimation
Stabilizing Subject Transfer in EEG Classification with Divergence Estimation
Niklas Smedemark-Margulies
Ye Wang
T. Koike-Akino
Jing Liu
K. Parsons
Yunus Bicer
Deniz Erdogmus
62
0
0
12 Oct 2023
On Imperfect Recall in Multi-Agent Influence Diagrams
On Imperfect Recall in Multi-Agent Influence Diagrams
James Fox
Matt MacDermott
Lewis Hammond
Paul Harrenstein
Alessandro Abate
Michael Wooldridge
85
4
0
11 Jul 2023
Containing a spread through sequential learning: to exploit or to
  explore?
Containing a spread through sequential learning: to exploit or to explore?
Xingran Chen
Hesam Nikpey
Jungyeol Kim
S. Sarkar
Shirin Saeedi Bidokhti
35
1
0
01 Mar 2023
Linear-Time Algorithms for Front-Door Adjustment in Causal Graphs
Linear-Time Algorithms for Front-Door Adjustment in Causal Graphs
Marcel Wienöbst
Benito van der Zander
Maciej Liskiewicz
CML
110
4
0
29 Nov 2022
A Complete Criterion for Value of Information in Soluble Influence
  Diagrams
A Complete Criterion for Value of Information in Soluble Influence Diagrams
Chris van Merwijk
Ryan Carey
Tom Everitt
72
5
0
23 Feb 2022
First-Order Context-Specific Likelihood Weighting in Hybrid
  Probabilistic Logic Programs
First-Order Context-Specific Likelihood Weighting in Hybrid Probabilistic Logic Programs
Nitesh Kumar
Ondrej Kuzelka
Luc de Raedt
28
3
0
26 Jan 2022
Agent Incentives: A Causal Perspective
Agent Incentives: A Causal Perspective
Tom Everitt
Ryan Carey
Eric D. Langlois
Pedro A. Ortega
Shane Legg
CML
74
56
0
02 Feb 2021
Once Upon A Time In Visualization: Understanding the Use of Textual
  Narratives for Causality
Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality
Arjun Choudhry
Mandar Sharma
Pramod Chundury
T. Kapler
Derek W. S. Gray
Naren Ramakrishnan
Niklas Elmqvist
52
23
0
06 Sep 2020
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust
  Inference
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference
Andac Demir
T. Koike-Akino
Ye Wang
Deniz Erdogmus
30
0
0
02 Jul 2020
Learning Distributional Programs for Relational Autocompletion
Learning Distributional Programs for Relational Autocompletion
Nitesh Kumar
Ondrej Kuzelka
Luc de Raedt
NAI
70
2
0
23 Jan 2020
A Survey on Document-level Neural Machine Translation: Methods and
  Evaluation
A Survey on Document-level Neural Machine Translation: Methods and Evaluation
Sameen Maruf
Fahimeh Saleh
Gholamreza Haffari
AI4TS
91
23
0
18 Dec 2019
Better Document-Level Machine Translation with Bayes' Rule
Better Document-Level Machine Translation with Bayes' Rule
Lei Yu
Laurent Sartran
Wojciech Stokowiec
Wang Ling
Lingpeng Kong
Phil Blunsom
Chris Dyer
79
7
0
01 Oct 2019
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in
  Heterogeneous Clusters
Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters
Subho Sankar Banerjee
Saurabh Jha
Zbigniew T. Kalbarczyk
Ravishankar Iyer
46
11
0
04 Sep 2019
Understanding Agent Incentives using Causal Influence Diagrams. Part I:
  Single Action Settings
Understanding Agent Incentives using Causal Influence Diagrams. Part I: Single Action Settings
Tom Everitt
Pedro A. Ortega
Elizabeth Barnes
Shane Legg
CML
60
0
0
26 Feb 2019
Kernel Density Estimation-Based Markov Models with Hidden State
Kernel Density Estimation-Based Markov Models with Hidden State
G. Henter
A. Leijon
W. Kleijn
21
1
0
30 Jul 2018
Probabilistic Warnings in National Security Crises: Pearl Harbor
  Revisited
Probabilistic Warnings in National Security Crises: Pearl Harbor Revisited
David M. Blum
M. Paté-Cornell
33
5
0
13 Feb 2018
A Rational Distributed Process-level Account of Independence Judgment
A Rational Distributed Process-level Account of Independence Judgment
A. S. Nobandegani
I. Psaromiligkos
23
1
0
30 Jan 2018
Detecting Dependencies in Sparse, Multivariate Databases Using
  Probabilistic Programming and Non-parametric Bayes
Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes
Feras A. Saad
Vikash K. Mansinghka
60
14
0
05 Nov 2016
Generalized Permutohedra from Probabilistic Graphical Models
Generalized Permutohedra from Probabilistic Graphical Models
F. Mohammadi
Caroline Uhler
Charles Wang
Josephine Yu
139
22
0
06 Jun 2016
Efficient Value of Information Computation
Efficient Value of Information Computation
Ross D. Shachter
70
58
0
23 Jan 2013
Welldefined Decision Scenarios
Welldefined Decision Scenarios
Thomas D. Nielsen
F. V. Jensen
77
67
0
23 Jan 2013
Pivotal Pruning of Trade-offs in QPNs
Pivotal Pruning of Trade-offs in QPNs
S. Renooij
L. V. D. Gaag
Simon Parsons
S. Green
TPM
58
14
0
16 Jan 2013
Evaluating Influence Diagrams using LIMIDs
Evaluating Influence Diagrams using LIMIDs
D. Nilsson
Steffen Lauritzen
71
44
0
16 Jan 2013
Probabilistic Models for Agents' Beliefs and Decisions
Probabilistic Models for Agents' Beliefs and Decisions
Brian Milch
D. Koller
68
31
0
16 Jan 2013
Unconstrained Influence Diagrams
Unconstrained Influence Diagrams
F. V. Jensen
M. Vomlelová
38
53
0
12 Dec 2012
Identifying the Relevant Nodes Without Learning the Model
Identifying the Relevant Nodes Without Learning the Model
J. Peña
R. Nilsson
J. Björkegren
Jesper N. Tegnér
CML
150
7
0
27 Jun 2012
Evaluating influence diagrams with decision circuits
Evaluating influence diagrams with decision circuits
D. Bhattacharjya
Ross D. Shachter
TPM
50
42
0
20 Jun 2012
Dynamic programming in in uence diagrams with decision circuits
Dynamic programming in in uence diagrams with decision circuits
Ross D. Shachter
D. Bhattacharjya
TPM
55
17
0
15 Mar 2012
Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective
Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective
J. Textor
Maciej Liskiewicz
CML
85
70
0
14 Feb 2012
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