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Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders

Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders

22 February 2024
Christian Toth
Christian Knoll
Franz Pernkopf
Robert Peharz
    CML
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Papers citing "Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders"

5 / 5 papers shown
Title
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs
Ryan Thompson
Edwin V. Bonilla
Robert Kohn
24
0
0
24 May 2024
Bayesian Causal Inference with Gaussian Process Networks
Bayesian Causal Inference with Gaussian Process Networks
Enrico Giudice
Jack Kuipers
G. Moffa
19
1
0
01 Feb 2024
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery
Chris Cundy
Aditya Grover
Stefano Ermon
CML
32
71
0
06 Dec 2021
Rao-Blackwellization in the MCMC era
Rao-Blackwellization in the MCMC era
Christian P. Robert
Gareth O. Roberts
25
9
0
04 Jan 2021
Exact Maximum Margin Structure Learning of Bayesian Networks
Exact Maximum Margin Structure Learning of Bayesian Networks
Robert Peharz
Franz Pernkopf
TPM
46
12
0
27 Jun 2012
1