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06/11/2023
A Penalized Poisson Likelihood Approach to High-Dimensional Semi-Parametric Inference for Doubly-Stochastic Point Processes
Doubly-stochastic point processes model the occurrence of events over a ...
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10/14/2022
Estimation of High-Dimensional Markov-Switching VAR Models with an Approximate EM Algorithm
Regime shifts in high-dimensional time series arise naturally in many ap...
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07/24/2022
Statistical inference for high-dimensional generalized estimating equations
We propose a novel inference procedure for linear combinations of high-d...
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09/23/2021
Joint Estimation and Inference for Multi-Experiment Networks of High-Dimensional Point Processes
Modern high-dimensional point process data, especially those from neuros...
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09/22/2021
Causal Discovery in High-Dimensional Point Process Networks with Hidden Nodes
Thanks to technological advances leading to near-continuous time observa...
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09/15/2021
Direct estimation of differential Granger causality between two high-dimensional time series
Differential Granger causality, that is understanding how Granger causal...
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09/10/2021
Interaction Models and Generalized Score Matching for Compositional Data
Applications such as the analysis of microbiome data have led to renewed...
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07/08/2021
Causal Structural Learning Via Local Graphs
We consider the problem of learning causal structures in sparse high-dim...
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06/21/2021
Nonparametric causal structure learning in high dimensions
The PC and FCI algorithms are popular constraint-based methods for learn...
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05/20/2021
Definite Non-Ancestral Relations and Structure Learning
In causal graphical models based on directed acyclic graphs (DAGs), dire...
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05/14/2021
Inference on function-valued parameters using a restricted score test
It is often of interest to make inference on an unknown function that is...
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05/05/2021
Granger Causality: A Review and Recent Advances
Introduced more than a half century ago, Granger causality has become a ...
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05/05/2021
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure
Originally developed for imputing missing entries in low rank, or approx...
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04/16/2021
Generalized Matrix Decomposition Regression: Estimation and Inference for Two-way Structured Data
This paper studies high-dimensional regression with two-way structured d...
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10/17/2020
Covariate-Adjusted Inference for Differential Analysis of High-Dimensional Networks
Differences between genetic networks corresponding to disease conditions...
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10/17/2020
Statistical Inference for Qualitative Interactions with Applications to Precision Medicine and Differential Network Analysis
Qualitative interactions occur when a treatment effect or measure of ass...
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09/24/2020
Generalized Score Matching for General Domains
Estimation of density functions supported on general domains arises when...
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07/15/2020
Statistical Inference for Networks of High-Dimensional Point Processes
Fueled in part by recent applications in neuroscience, the multivariate ...
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05/29/2020
Consistent Second-Order Conic Integer Programming for Learning Bayesian Networks
Bayesian Networks (BNs) represent conditional probability relations amon...
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04/08/2020
Directed Graphical Models and Causal Discovery for Zero-Inflated Data
Modern RNA sequencing technologies provide gene expression measurements ...
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03/09/2020
Differential Network Analysis: A Statistical Perspective
Networks effectively capture interactions among components of complex sy...
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12/16/2019
Statistical significance in high-dimensional linear mixed models
This paper concerns the development of an inferential framework for high...
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09/30/2019
Network Differential Connectivity Analysis
Identifying differences in networks has become a canonical problem in ma...
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04/23/2019
Integer Programming for Learning Directed Acyclic Graphs from Continuous Data
Learning directed acyclic graphs (DAGs) from data is a challenging task ...
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03/11/2019
Generalized Sparse Additive Models
We present a unified framework for estimation and analysis of generalize...
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03/11/2019
Wavelet regression and additive models for irregularly spaced data
We present a novel approach for nonparametric regression using wavelet b...
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12/26/2018
Generalized Score Matching for Non-Negative Data
A common challenge in estimating parameters of probability density funct...
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06/16/2018
The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks
We consider the task of estimating a high-dimensional directed acyclic g...
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02/18/2018
Graphical Models for Non-Negative Data Using Generalized Score Matching
A common challenge in estimating parameters of probability density funct...
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02/16/2018
Neural Granger Causality for Nonlinear Time Series
While most classical approaches to Granger causality detection assume li...
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11/22/2017
An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Series
We present an efficient alternating direction method of multipliers (ADM...
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11/22/2017
An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality Discovery
While most classical approaches to Granger causality detection repose up...
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11/17/2017
Joint Structural Break Detection and Parameter Estimation in High-Dimensional Non-Stationary VAR Models
Assuming stationarity is unrealistic in many time series applications. A...
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01/02/2016
Joint Estimation of Precision Matrices in Heterogeneous Populations
We introduce a general framework for estimation of inverse covariance, o...
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01/12/2014
Inference in High Dimensions with the Penalized Score Test
In recent years, there has been considerable theoretical development reg...
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12/02/2013
Inferring Regulatory Networks by Combining Perturbation Screens and Steady State Gene Expression Profiles
Reconstructing transcriptional regulatory networks is an important task ...
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07/19/2013
The Cluster Graphical Lasso for improved estimation of Gaussian graphical models
We consider the task of estimating a Gaussian graphical model in the hig...
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11/28/2009