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Structure Learning in Graphical Modeling

Structure Learning in Graphical Modeling

7 June 2016
Mathias Drton
Marloes H. Maathuis
    CML
ArXivPDFHTML

Papers citing "Structure Learning in Graphical Modeling"

35 / 35 papers shown
Title
Model-free Estimation of Latent Structure via Multiscale Nonparametric Maximum Likelihood
Model-free Estimation of Latent Structure via Multiscale Nonparametric Maximum Likelihood
Bryon Aragam
Ruiyi Yang
40
0
0
29 Oct 2024
Discrete distributions are learnable from metastable samples
Discrete distributions are learnable from metastable samples
Abhijith Jayakumar
A. Lokhov
Sidhant Misra
Marc Vuffray
37
1
0
17 Oct 2024
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching
Daniel J. Williams
Leyang Wang
Qizhen Ying
Song Liu
Mladen Kolar
32
1
0
14 Oct 2024
Parameter identification in linear non-Gaussian causal models under
  general confounding
Parameter identification in linear non-Gaussian causal models under general confounding
D. Tramontano
Mathias Drton
Jalal Etesami
CML
37
1
0
31 May 2024
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models
Tong Xu
Armeen Taeb
Simge Kuccukyavuz
Ali Shojaie
CML
36
1
0
19 Apr 2024
Computational Hypergraph Discovery, a Gaussian Process framework for
  connecting the dots
Computational Hypergraph Discovery, a Gaussian Process framework for connecting the dots
Théo Bourdais
Pau Batlle
Xianjin Yang
Ricardo Baptista
Nicolas Rouquette
H. Owhadi
16
0
0
28 Nov 2023
Model Selection over Partially Ordered Sets
Model Selection over Partially Ordered Sets
Armeen Taeb
Peter Bühlmann
V. Chandrasekaran
14
5
0
20 Aug 2023
Learning the hub graphical Lasso model with the structured sparsity via an efficient algorithm
Learning the hub graphical Lasso model with the structured sparsity via an efficient algorithm
Chengjing Wang
Peipei Tang
Wen-Bin He
Meixia Lin
33
0
0
17 Aug 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment
  Effect Estimation
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
Chris C. Emezue
Alexandre Drouin
T. Deleu
Stefan Bauer
Yoshua Bengio
CML
24
2
0
11 Jul 2023
$\texttt{causalAssembly}$: Generating Realistic Production Data for
  Benchmarking Causal Discovery
causalAssembly\texttt{causalAssembly}causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery
Konstantin Göbler
Tobias Windisch
Mathias Drton
T. Pychynski
Steffen Sonntag
Martin Roth
CML
65
9
0
19 Jun 2023
The Functional Graphical Lasso
The Functional Graphical Lasso
Kartik G. Waghmare
T. Masak
V. Panaretos
6
1
0
04 Jun 2023
Maximum a Posteriori Estimation in Graphical Models Using Local Linear
  Approximation
Maximum a Posteriori Estimation in Graphical Models Using Local Linear Approximation
K. Sagar
J. Datta
Sayantan Banerjee
A. Bhadra
18
2
0
13 Mar 2023
Ensemble transport smoothing. Part II: Nonlinear updates
Ensemble transport smoothing. Part II: Nonlinear updates
M. Ramgraber
Ricardo Baptista
D. McLaughlin
Youssef Marzouk
13
6
0
31 Oct 2022
Learning Linear Non-Gaussian Polytree Models
Learning Linear Non-Gaussian Polytree Models
D. Tramontano
Anthea Monod
Mathias Drton
29
7
0
13 Aug 2022
Valid Inference after Causal Discovery
Valid Inference after Causal Discovery
Paula Gradu
Tijana Zrnic
Yixin Wang
Michael I. Jordan
CML
26
8
0
11 Aug 2022
Learning Graph Structure from Convolutional Mixtures
Learning Graph Structure from Convolutional Mixtures
Max Wasserman
Saurabh Sihag
Gonzalo Mateos
Alejandro Ribeiro
GNN
CML
BDL
37
6
0
19 May 2022
Order-based Structure Learning without Score Equivalence
Order-based Structure Learning without Score Equivalence
Hyunwoong Chang
James Cai
Quan Zhou
CML
OffRL
16
3
0
10 Feb 2022
Distributed Learning of Generalized Linear Causal Networks
Distributed Learning of Generalized Linear Causal Networks
Qiaoling Ye
Arash A. Amini
Qing Zhou
CML
OOD
AI4CE
25
16
0
23 Jan 2022
Decentralized Learning of Tree-Structured Gaussian Graphical Models from
  Noisy Data
Decentralized Learning of Tree-Structured Gaussian Graphical Models from Noisy Data
Akram Hussain
14
0
0
22 Sep 2021
WiseR: An end-to-end structure learning and deployment framework for
  causal graphical models
WiseR: An end-to-end structure learning and deployment framework for causal graphical models
Shubham Maheshwari
Khushbu Pahwa
Tavpritesh Sethi
CML
16
1
0
16 Aug 2021
Efficient and Scalable Structure Learning for Bayesian Networks:
  Algorithms and Applications
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications
Rong Zhu
A. Pfadler
Ziniu Wu
Yuxing Han
Xiaoke Yang
Feng Ye
Zhenping Qian
Jingren Zhou
Bin Cui
14
9
0
07 Dec 2020
Differential Network Analysis: A Statistical Perspective
Differential Network Analysis: A Statistical Perspective
Ali Shojaie
33
48
0
09 Mar 2020
Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble
  Method
Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method
Pengzhou (Abel) Wu
Kenji Fukumizu
CML
17
26
0
07 Jan 2020
Direct Estimation of Differential Functional Graphical Models
Direct Estimation of Differential Functional Graphical Models
Boxin Zhao
Y Samuel Wang
Mladen Kolar
19
15
0
22 Oct 2019
On Testing Marginal versus Conditional Independence
On Testing Marginal versus Conditional Independence
F. R. Guo
Thomas S. Richardson
67
5
0
05 Jun 2019
Predictive Learning on Hidden Tree-Structured Ising Models
Predictive Learning on Hidden Tree-Structured Ising Models
Konstantinos E. Nikolakakis
Dionysios S. Kalogerias
Anand D. Sarwate
18
12
0
11 Dec 2018
Graphical Models for Extremes
Graphical Models for Extremes
Sebastian Engelke
Adrien Hitz
14
110
0
04 Dec 2018
Algebraic Equivalence of Linear Structural Equation Models
Algebraic Equivalence of Linear Structural Equation Models
T. V. Ommen
Joris M. Mooij
30
5
0
10 Jul 2018
On Causal Discovery with Equal Variance Assumption
On Causal Discovery with Equal Variance Assumption
Wenyu Chen
Mathias Drton
Y Samuel Wang
CML
14
84
0
09 Jul 2018
Computation of maximum likelihood estimates in cyclic structural
  equation models
Computation of maximum likelihood estimates in cyclic structural equation models
Mathias Drton
C. Fox
Y Samuel Wang
27
16
0
11 Oct 2016
Robust estimators for non-decomposable elliptical graphical models
Robust estimators for non-decomposable elliptical graphical models
D. Vogel
David E. Tyler
46
11
0
21 Feb 2013
Causal Inference in the Presence of Latent Variables and Selection Bias
Causal Inference in the Presence of Latent Variables and Selection Bias
Peter Spirtes
Christopher Meek
Thomas S. Richardson
CML
141
434
0
20 Feb 2013
A Discovery Algorithm for Directed Cyclic Graphs
A Discovery Algorithm for Directed Cyclic Graphs
Thomas S. Richardson
CML
75
193
0
13 Feb 2013
Discovering Graphical Granger Causality Using the Truncating Lasso
  Penalty
Discovering Graphical Granger Causality Using the Truncating Lasso Penalty
Ali Shojaie
George Michailidis
CML
68
214
0
03 Jul 2010
Time Varying Undirected Graphs
Time Varying Undirected Graphs
Shuheng Zhou
John D. Lafferty
Larry A. Wasserman
114
240
0
20 Feb 2008
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