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The Nonparanormal SKEPTIC

The Nonparanormal SKEPTIC

27 June 2012
Han Liu
Fang Han
M. Yuan
John D. Lafferty
Larry A. Wasserman
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Papers citing "The Nonparanormal SKEPTIC"

50 / 66 papers shown
Title
Academic Network Representation via Prediction-Sampling Incorporated Tensor Factorization
Academic Network Representation via Prediction-Sampling Incorporated Tensor Factorization
Chunyang Zhang
Xin Liao
Hao Wu
37
0
0
11 Apr 2025
Efficient learning of differential network in multi-source
  non-paranormal graphical models
Efficient learning of differential network in multi-source non-paranormal graphical models
Mojtaba Nikahd
Seyed Abolfazl Motahari
20
0
0
03 Oct 2024
Sub-Gaussian High-Dimensional Covariance Matrix Estimation under
  Elliptical Factor Model with 2 + εth Moment
Sub-Gaussian High-Dimensional Covariance Matrix Estimation under Elliptical Factor Model with 2 + εth Moment
Yi Ding
Xinghua Zheng
32
0
0
26 Jun 2024
Greedy equivalence search for nonparametric graphical models
Greedy equivalence search for nonparametric graphical models
Bryon Aragam
CML
38
1
0
25 Jun 2024
Property testing in graphical models: testing small separation numbers
Property testing in graphical models: testing small separation numbers
Luc Devroye
Gábor Lugosi
Piotr Zwiernik
22
0
0
16 May 2024
Learning Directed Acyclic Graphs from Partial Orderings
Learning Directed Acyclic Graphs from Partial Orderings
Ali Shojaie
Wenyu Chen
CML
45
0
0
24 Mar 2024
On Sufficient Graphical Models
On Sufficient Graphical Models
Bing Li
Kyongwon Kim
22
0
0
10 Jul 2023
Entropic covariance models
Entropic covariance models
Piotr Zwiernik
22
2
0
06 Jun 2023
Nonparanormal Graph Quilting with Applications to Calcium Imaging
Nonparanormal Graph Quilting with Applications to Calcium Imaging
Andersen Chang
Lili Zheng
Gautam Dasarathy
Genevera I. Allen
19
1
0
22 May 2023
Module-based regularization improves Gaussian graphical models when
  observing noisy data
Module-based regularization improves Gaussian graphical models when observing noisy data
Magnus Neuman
J. Calatayud
Viktor Tasselius
M. Rosvall
20
1
0
29 Mar 2023
High-Dimensional Undirected Graphical Models for Arbitrary Mixed Data
High-Dimensional Undirected Graphical Models for Arbitrary Mixed Data
Konstantin Göbler
Anne Miloschewski
Mathias Drton
S. Mukherjee
21
2
0
21 Nov 2022
Inferring independent sets of Gaussian variables after thresholding
  correlations
Inferring independent sets of Gaussian variables after thresholding correlations
Arkajyoti Saha
Daniela Witten
Jacob Bien
24
3
0
02 Nov 2022
Graphical Model Inference with Erosely Measured Data
Graphical Model Inference with Erosely Measured Data
Lili Zheng
Genevera I. Allen
13
1
0
20 Oct 2022
Low-Rank Covariance Completion for Graph Quilting with Applications to
  Functional Connectivity
Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity
Andersen Chang
Lili Zheng
Genevera I. Allen
16
3
0
17 Sep 2022
Neural Copula: A unified framework for estimating generic
  high-dimensional Copula functions
Neural Copula: A unified framework for estimating generic high-dimensional Copula functions
Zhi Zeng
Ting Wang
9
5
0
23 May 2022
Scalable Bigraphical Lasso: Two-way Sparse Network Inference for Count
  Data
Scalable Bigraphical Lasso: Two-way Sparse Network Inference for Count Data
Sijia Li
Martín López-García
Neil D. Lawrence
Luisa Cutillo
32
5
0
15 Mar 2022
Estimating Gaussian Copulas with Missing Data
Estimating Gaussian Copulas with Missing Data
Maximilian Kertel
Markus Pauly
23
3
0
14 Jan 2022
The folded concave Laplacian spectral penalty learns block diagonal
  sparsity patterns with the strong oracle property
The folded concave Laplacian spectral penalty learns block diagonal sparsity patterns with the strong oracle property
Iain Carmichael
32
2
0
07 Jul 2021
A unified precision matrix estimation framework via sparse column-wise
  inverse operator under weak sparsity
A unified precision matrix estimation framework via sparse column-wise inverse operator under weak sparsity
Zeyu Wu
Cheng-Long Wang
Weidong Liu
36
3
0
07 Jul 2021
The Variational Bayesian Inference for Network Autoregression Models
The Variational Bayesian Inference for Network Autoregression Models
Wei Lai
Ray-Bing Chen
Ying Chen
Thorsten Koch
12
0
0
18 Feb 2021
Learning Continuous Exponential Families Beyond Gaussian
Learning Continuous Exponential Families Beyond Gaussian
C. Ren
Sidhant Misra
Marc Vuffray
A. Lokhov
39
5
0
18 Feb 2021
Locally associated graphical models and mixed convex exponential
  families
Locally associated graphical models and mixed convex exponential families
Steffen Lauritzen
Piotr Zwiernik
19
11
0
11 Aug 2020
Robust Estimation of Tree Structured Ising Models
Robust Estimation of Tree Structured Ising Models
A. Katiyar
Vatsal Shah
C. Caramanis
TPM
24
10
0
10 Jun 2020
Bayesian Semi-supervised learning under nonparanormality
Bayesian Semi-supervised learning under nonparanormality
Rui Zhu
Shuvrarghya Ghosh
S. Ghosal
6
0
0
11 Jan 2020
Structure recovery for partially observed discrete Markov random fields
  on graphs under not necessarily positive distributions
Structure recovery for partially observed discrete Markov random fields on graphs under not necessarily positive distributions
Florencia Leonardi
Rodrigo Carvalho
22
2
0
27 Nov 2019
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula
  Processes
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
David Salinas
Michael Bohlke-Schneider
Laurent Callot
Roberto Medico
Jan Gasthaus
AI4TS
30
224
0
07 Oct 2019
Learning partial correlation graphs and graphical models by covariance
  queries
Learning partial correlation graphs and graphical models by covariance queries
Gábor Lugosi
J. Truszkowski
Vasiliki Velona
Piotr Zwiernik
8
6
0
22 Jun 2019
Learning Gaussian Graphical Models with Ordered Weighted L1
  Regularization
Learning Gaussian Graphical Models with Ordered Weighted L1 Regularization
Cody Mazza-Anthony
Bogdan Mazoure
Mark J. Coates
22
3
0
06 Jun 2019
Nonparametric Density Estimation for High-Dimensional Data - Algorithms
  and Applications
Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications
Zhipeng Wang
D. W. Scott
24
69
0
30 Mar 2019
High Dimensional Robust $M$-Estimation: Arbitrary Corruption and Heavy
  Tails
High Dimensional Robust MMM-Estimation: Arbitrary Corruption and Heavy Tails
L. Liu
Tianyang Li
C. Caramanis
21
14
0
24 Jan 2019
Generalized Score Matching for Non-Negative Data
Generalized Score Matching for Non-Negative Data
Shiqing Yu
Mathias Drton
Ali Shojaie
24
2
0
26 Dec 2018
Learning high-dimensional graphical models with regularized quadratic
  scoring
Learning high-dimensional graphical models with regularized quadratic scoring
Eric Janofsky
19
1
0
15 Sep 2018
Structure Learning of Markov Random Fields through Grow-Shrink Maximum
  Pseudolikelihood Estimation
Structure Learning of Markov Random Fields through Grow-Shrink Maximum Pseudolikelihood Estimation
Yuya Takashina
Shuyo Nakatani
Masato Inoue
12
0
0
03 Jul 2018
High-Dimensional Inference for Cluster-Based Graphical Models
High-Dimensional Inference for Cluster-Based Graphical Models
Carson Eisenach
F. Bunea
Y. Ning
Claudiu Dinicu
14
8
0
13 Jun 2018
Finding Differentially Covarying Needles in a Temporally Evolving
  Haystack: A Scan Statistics Perspective
Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective
Ronak R. Mehta
Hyunwoo J. Kim
Shulei Wang
Sterling C. Johnson
Ming Yuan
Vikas Singh
26
0
0
20 Nov 2017
Inter-Subject Analysis: Inferring Sparse Interactions with Dense
  Intra-Graphs
Inter-Subject Analysis: Inferring Sparse Interactions with Dense Intra-Graphs
Cong Ma
Junwei Lu
Han Liu
16
8
0
20 Sep 2017
Learning non-parametric Markov networks with mutual information
Learning non-parametric Markov networks with mutual information
Janne Leppä-aho
Santeri Räisänen
Xiao Yang
Teemu Roos
21
2
0
08 Aug 2017
Nonparanormal Information Estimation
Nonparanormal Information Estimation
Shashank Singh
Barnabás Póczós
21
20
0
24 Feb 2017
Communication-efficient Distributed Estimation and Inference for
  Transelliptical Graphical Models
Communication-efficient Distributed Estimation and Inference for Transelliptical Graphical Models
Pan Xu
Lu Tian
Quanquan Gu
FedML
21
7
0
29 Dec 2016
Indirect Gaussian Graph Learning beyond Gaussianity
Indirect Gaussian Graph Learning beyond Gaussianity
Yiyuan She
Shao Tang
Qiaoya Zhang
26
3
0
08 Oct 2016
An Exponential Inequality for U-Statistics under Mixing Conditions
An Exponential Inequality for U-Statistics under Mixing Conditions
Fang Han
27
24
0
22 Sep 2016
Graphical Models for Discrete and Continuous Data
Graphical Models for Discrete and Continuous Data
Rui Zhuang
Noah Simon
Johannes Lederer
18
4
0
18 Sep 2016
Information Theoretic Structure Learning with Confidence
Information Theoretic Structure Learning with Confidence
Kevin R. Moon
M. Noshad
Salimeh Yasaei Sekeh
Alfred Hero
19
18
0
13 Sep 2016
A Review of Multivariate Distributions for Count Data Derived from the
  Poisson Distribution
A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution
David I. Inouye
Eunho Yang
Genevera I. Allen
Pradeep Ravikumar
28
112
0
31 Aug 2016
Joint Estimation of Multiple Dependent Gaussian Graphical Models with
  Applications to Mouse Genomics
Joint Estimation of Multiple Dependent Gaussian Graphical Models with Applications to Mouse Genomics
Yuying Xie
Yufeng Liu
W. Valdar
25
26
0
30 Aug 2016
Structure Learning in Graphical Modeling
Structure Learning in Graphical Modeling
Mathias Drton
Marloes H. Maathuis
CML
44
246
0
07 Jun 2016
Post-Regularization Inference for Time-Varying Nonparanormal Graphical
  Models
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models
Junwei Lu
Mladen Kolar
Han Liu
22
9
0
28 Dec 2015
Structure estimation for mixed graphical models in high-dimensional data
Structure estimation for mixed graphical models in high-dimensional data
Jonas M. B. Haslbeck
L. Waldorp
CML
26
47
0
19 Oct 2015
Sufficient Forecasting Using Factor Models
Sufficient Forecasting Using Factor Models
Jianqing Fan
Lingzhou Xue
Jiawei Yao
AI4TS
42
76
0
27 May 2015
Graphical Fermat's Principle and Triangle-Free Graph Estimation
Graphical Fermat's Principle and Triangle-Free Graph Estimation
Junwei Lu
Han Liu
24
0
0
23 Apr 2015
12
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