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1606.02359
Cited By
Structure Learning in Graphical Modeling
7 June 2016
Mathias Drton
Marloes H. Maathuis
CML
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Papers citing
"Structure Learning in Graphical Modeling"
35 / 35 papers shown
Title
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
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
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
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
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
Théo Bourdais
Pau Batlle
Xianjin Yang
Ricardo Baptista
Nicolas Rouquette
H. Owhadi
16
0
0
28 Nov 2023
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
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
Chris C. Emezue
Alexandre Drouin
T. Deleu
Stefan Bauer
Yoshua Bengio
CML
24
2
0
11 Jul 2023
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
Kartik G. Waghmare
T. Masak
V. Panaretos
6
1
0
04 Jun 2023
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
M. Ramgraber
Ricardo Baptista
D. McLaughlin
Youssef Marzouk
13
6
0
31 Oct 2022
Learning Linear Non-Gaussian Polytree Models
D. Tramontano
Anthea Monod
Mathias Drton
29
7
0
13 Aug 2022
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
Max Wasserman
Saurabh Sihag
Gonzalo Mateos
Alejandro Ribeiro
GNN
CML
BDL
37
6
0
19 May 2022
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
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
Akram Hussain
14
0
0
22 Sep 2021
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
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
Ali Shojaie
33
48
0
09 Mar 2020
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
Boxin Zhao
Y Samuel Wang
Mladen Kolar
19
15
0
22 Oct 2019
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
Konstantinos E. Nikolakakis
Dionysios S. Kalogerias
Anand D. Sarwate
18
12
0
11 Dec 2018
Graphical Models for Extremes
Sebastian Engelke
Adrien Hitz
14
110
0
04 Dec 2018
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
Wenyu Chen
Mathias Drton
Y Samuel Wang
CML
14
84
0
09 Jul 2018
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
D. Vogel
David E. Tyler
46
11
0
21 Feb 2013
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
Thomas S. Richardson
CML
75
193
0
13 Feb 2013
Discovering Graphical Granger Causality Using the Truncating Lasso Penalty
Ali Shojaie
George Michailidis
CML
68
214
0
03 Jul 2010
Time Varying Undirected Graphs
Shuheng Zhou
John D. Lafferty
Larry A. Wasserman
114
240
0
20 Feb 2008
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