
Interaction Models and Generalized Score Matching for Compositional Data
Applications such as the analysis of microbiome data have led to renewed...
read it

Causal Structural Learning Via Local Graphs
We consider the problem of learning causal structures in sparse highdim...
read it

Nonparametric causal structure learning in high dimensions
The PC and FCI algorithms are popular constraintbased methods for learn...
read it

Definite NonAncestral Relations and Structure Learning
In causal graphical models based on directed acyclic graphs (DAGs), dire...
read it

Inference on functionvalued parameters using a restricted score test
It is often of interest to make inference on an unknown function that is...
read it

Granger Causality: A Review and Recent Advances
Introduced more than a half century ago, Granger causality has become a ...
read it

On the Optimality of Nuclearnormbased Matrix Completion for Problems with Smooth Nonlinear Structure
Originally developed for imputing missing entries in low rank, or approx...
read it

Generalized Matrix Decomposition Regression: Estimation and Inference for Twoway Structured Data
This paper studies highdimensional regression with twoway structured d...
read it

CovariateAdjusted Inference for Differential Analysis of HighDimensional Networks
Differences between genetic networks corresponding to disease conditions...
read it

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...
read it

Generalized Score Matching for General Domains
Estimation of density functions supported on general domains arises when...
read it

Statistical Inference for Networks of HighDimensional Point Processes
Fueled in part by recent applications in neuroscience, the multivariate ...
read it

Consistent SecondOrder Conic Integer Programming for Learning Bayesian Networks
Bayesian Networks (BNs) represent conditional probability relations amon...
read it

Directed Graphical Models and Causal Discovery for ZeroInflated Data
Modern RNA sequencing technologies provide gene expression measurements ...
read it

Differential Network Analysis: A Statistical Perspective
Networks effectively capture interactions among components of complex sy...
read it

Statistical significance in highdimensional linear mixed models
This paper concerns the development of an inferential framework for high...
read it

Network Differential Connectivity Analysis
Identifying differences in networks has become a canonical problem in ma...
read it

Integer Programming for Learning Directed Acyclic Graphs from Continuous Data
Learning directed acyclic graphs (DAGs) from data is a challenging task ...
read it

Generalized Sparse Additive Models
We present a unified framework for estimation and analysis of generalize...
read it

Wavelet regression and additive models for irregularly spaced data
We present a novel approach for nonparametric regression using wavelet b...
read it

Generalized Score Matching for NonNegative Data
A common challenge in estimating parameters of probability density funct...
read it

The Reduced PCAlgorithm: Improved Causal Structure Learning in Large Random Networks
We consider the task of estimating a highdimensional directed acyclic g...
read it

Graphical Models for NonNegative Data Using Generalized Score Matching
A common challenge in estimating parameters of probability density funct...
read it

Neural Granger Causality for Nonlinear Time Series
While most classical approaches to Granger causality detection assume li...
read it

An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Series
We present an efficient alternating direction method of multipliers (ADM...
read it

An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality Discovery
While most classical approaches to Granger causality detection repose up...
read it

Joint Structural Break Detection and Parameter Estimation in HighDimensional NonStationary VAR Models
Assuming stationarity is unrealistic in many time series applications. A...
read it

Joint Estimation of Precision Matrices in Heterogeneous Populations
We introduce a general framework for estimation of inverse covariance, o...
read it

Inference in High Dimensions with the Penalized Score Test
In recent years, there has been considerable theoretical development reg...
read it

Inferring Regulatory Networks by Combining Perturbation Screens and Steady State Gene Expression Profiles
Reconstructing transcriptional regulatory networks is an important task ...
read it

The Cluster Graphical Lasso for improved estimation of Gaussian graphical models
We consider the task of estimating a Gaussian graphical model in the hig...
read it

Penalized Likelihood Methods for Estimation of Sparse High Dimensional Directed Acyclic Graphs
Directed acyclic graphs (DAGs) are commonly used to represent causal rel...
read it
Ali Shojaie
is this you? claim profile