Modelling the interactions between discrete and continuous causal factors in Bayesian networks

Inference in multi-agent causal models

Maes, Sam
Meganck, Stijn
Manderick, Bernard

October 2007

AbstractIn this article, we demonstrate the usefulness of causal Bayesian networks as probabilistic ...

Modeling Bayesian Networks by Learning from Experts

Wiegerinck, W.A.J.J.

January 2005

Contains fulltext : 32747.pdf (preprint version ) (Open Access)BNAIC'0

Advances to Bayesian network inference for generating causal networks from observational biological data

Yu, Jing
Smith, Victoria Anne
Wang, Paul P
Hartemink, Alexander J
Jarvis, Erich D

December 2004

Motivation: Network inference algorithms are powerful computational tools for identifying putative c...

Modeling the Interactions between Discrete and Continuous Causal Factors in Bayesian Networks

Lucas, P.J.F.
Hommersom, A.J.

January 2015

Contains fulltext : 139687.pdf (preprint version ) (Open Access

Modelling the interactions between discrete and continuous causal factors in Bayesian networks

Peter J. F. Lucas
Arjen Hommersom

January 2010

The theory of causal independence is frequently used to facilitate the assessment of the probabilist...

Exploiting Causal Independence in Large Bayesian Networks

Jurgelenaite, R.
Lucas, P.J.F.

January 2005

Contains fulltext : 32493.pdf (publisher's version ) (Closed access

1.2 Causal Bayesian Networks................................ 2

Changsung Kang
Changsung Kang
Vasant Honavar
Jack Lutz
Dimitris Margaritis
Alicia Carriquiry

January 2008

Part of the Computer Sciences Commons This Dissertation is brought to you for free and open access b...

Bayesian network modelling by qualitative patterns

Lucas, P.J.F.

January 2002

Contains fulltext : 112473.pdf (preprint version ) (Open Access

Noisy Threshold Functions for Modelling Causal Independence in Bayesian Networks

Jurgelenaite, R.
Heskes, T.M.
Lucas, P.J.F.

January 2006

Contains fulltext : 35578.pdf (preprint version ) (Open Access)19 p p

Bayesian network modelling through qualitative patterns

Lucas, P.J.F.

January 2005

Contains fulltext : 33263.pdf (publisher's version ) (Closed access

Causal Interaction in Bayesian Networks

Charles R. Twardy
Kevin B. Korb

January 2002

this paper another misguided attempt to reduce causation to probability. But causation leaves a dist...

The hidden elegance of causal interaction models

Renooij, S.
van der Gaag, L.C.
Ben Amor, N
Quost, B
Theobald, M

December 2019

Causal interaction models such as the noisy-or model, are used in Bayesian networks to simplify prob...

Towards an Integral Approach for Modeling Causality

Meganck, Stijn

September 2008

From conventional observation data , it is rarely possible to determine a fully causal Bayesian netw...

Dynamic bayesian networks: A factored model of probabilistic dynamics

Palaniappan, S.K.
Thiagarajan, P.S.

January 2012

10.1007/978-3-642-33386-6_2Lecture Notes in Computer Science (including subseries Lecture Notes in A...

Explaining data using causal Bayesian networks

Jaime

November 2020

We introduce Causal Bayesian Networks as a formalism for representing and explaining probabilistic c...

Inference in multi-agent causal models

Maes, Sam
Meganck, Stijn
Manderick, Bernard

October 2007

AbstractIn this article, we demonstrate the usefulness of causal Bayesian networks as probabilistic ...

Modeling Bayesian Networks by Learning from Experts

Wiegerinck, W.A.J.J.

January 2005

Contains fulltext : 32747.pdf (preprint version ) (Open Access)BNAIC'0

Advances to Bayesian network inference for generating causal networks from observational biological data

Yu, Jing
Smith, Victoria Anne
Wang, Paul P
Hartemink, Alexander J
Jarvis, Erich D

December 2004

Motivation: Network inference algorithms are powerful computational tools for identifying putative c...

Modeling the Interactions between Discrete and Continuous Causal Factors in Bayesian Networks

Lucas, P.J.F.
Hommersom, A.J.

January 2015

Contains fulltext : 139687.pdf (preprint version ) (Open Access

Modelling the interactions between discrete and continuous causal factors in Bayesian networks

Peter J. F. Lucas
Arjen Hommersom

January 2010

The theory of causal independence is frequently used to facilitate the assessment of the probabilist...

Exploiting Causal Independence in Large Bayesian Networks

Jurgelenaite, R.
Lucas, P.J.F.

January 2005

Contains fulltext : 32493.pdf (publisher's version ) (Closed access

1.2 Causal Bayesian Networks................................ 2

Changsung Kang
Changsung Kang
Vasant Honavar
Jack Lutz
Dimitris Margaritis
Alicia Carriquiry

January 2008

Part of the Computer Sciences Commons This Dissertation is brought to you for free and open access b...

Bayesian network modelling by qualitative patterns

Lucas, P.J.F.

January 2002

Contains fulltext : 112473.pdf (preprint version ) (Open Access

Noisy Threshold Functions for Modelling Causal Independence in Bayesian Networks

Jurgelenaite, R.
Heskes, T.M.
Lucas, P.J.F.

January 2006

Contains fulltext : 35578.pdf (preprint version ) (Open Access)19 p p

Bayesian network modelling through qualitative patterns

Lucas, P.J.F.

January 2005

Contains fulltext : 33263.pdf (publisher's version ) (Closed access

Causal Interaction in Bayesian Networks

Charles R. Twardy
Kevin B. Korb

January 2002

this paper another misguided attempt to reduce causation to probability. But causation leaves a dist...

The hidden elegance of causal interaction models

Renooij, S.
van der Gaag, L.C.
Ben Amor, N
Quost, B
Theobald, M

December 2019

Causal interaction models such as the noisy-or model, are used in Bayesian networks to simplify prob...

Towards an Integral Approach for Modeling Causality

Meganck, Stijn

September 2008

From conventional observation data , it is rarely possible to determine a fully causal Bayesian netw...

Dynamic bayesian networks: A factored model of probabilistic dynamics

Palaniappan, S.K.
Thiagarajan, P.S.

January 2012

10.1007/978-3-642-33386-6_2Lecture Notes in Computer Science (including subseries Lecture Notes in A...

Explaining data using causal Bayesian networks

Jaime

November 2020

We introduce Causal Bayesian Networks as a formalism for representing and explaining probabilistic c...

Inference in multi-agent causal models

Maes, Sam
Meganck, Stijn
Manderick, Bernard

October 2007

AbstractIn this article, we demonstrate the usefulness of causal Bayesian networks as probabilistic ...

Modeling Bayesian Networks by Learning from Experts

Wiegerinck, W.A.J.J.

January 2005

Contains fulltext : 32747.pdf (preprint version ) (Open Access)BNAIC'0

Advances to Bayesian network inference for generating causal networks from observational biological data

Yu, Jing
Smith, Victoria Anne
Wang, Paul P
Hartemink, Alexander J
Jarvis, Erich D

December 2004

Motivation: Network inference algorithms are powerful computational tools for identifying putative c...

Modelling the interactions between discrete and continuous causal factors in Bayesian networks

Abstract

Extracted data

Modelling the interactions between discrete and continuous causal factors in Bayesian networks

Abstract

Extracted data

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