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07/26/2023
Learning sources of variability from high-dimensional observational studies
Causal inference studies whether the presence of a variable influences a...
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05/03/2023
Discovering Communication Pattern Shifts in Large-Scale Networks using Encoder Embedding and Vertex Dynamics
The analysis of large-scale time-series network data, such as social med...
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03/31/2023
Synergistic Graph Fusion via Encoder Embedding
In this paper, we introduce a novel approach to multi-graph embedding ca...
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01/18/2023
Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection
In this paper we propose a novel and computationally efficient method to...
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09/27/2021
Graph Encoder Embedding
In this paper we propose a lightning fast graph embedding method called ...
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10/25/2020
A Simple Spectral Failure Mode for Graph Convolutional Networks
We present a simple generative model in which spectral graph embedding f...
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01/04/2020
High-Dimensional Independence Testing and Maximum Marginal Correlation
A number of universally consistent dependence measures have been recentl...
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12/27/2019
The Chi-Square Test of Distance Correlation
Distance correlation has gained much recent attention in the statistics ...
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10/20/2019
The Exact Equivalence of Independence Testing and Two-Sample Testing
Testing independence and testing equality of distributions are two tight...
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08/18/2019
A Consistent Independence Test for Multivariate Time-Series
A fundamental problem in statistical data analysis is testing whether tw...
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07/03/2019
hyppo: A Comprehensive Multivariate Hypothesis Testing Python Package
We introduce hyppo, a unified library for performing multivariate hypoth...
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07/03/2019
mgcpy: A Comprehensive High Dimensional Independence Testing Python Package
With the increase in the amount of data in many fields, a method to cons...
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06/30/2019
Estimating Information-Theoretic Quantities with Random Forests
Information-theoretic quantities, such as mutual information and conditi...
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06/09/2019
Graph Independence Testing
Identifying statistically significant dependency between variables is a ...
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06/04/2019
Sparse Representation Classification via Screening for Graphs
The sparse representation classifier (SRC) is shown to work well for ima...
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11/30/2018
Decision Forests Induce Characteristic Kernels
Decision forests are popular tools for classification and regression. Th...
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06/14/2018
The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing
Distance-based methods, also called "energy statistics", are leading met...
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01/23/2018
Signal Subgraph Estimation Via Vertex Screening
Graph classification and regression have wide applications in a variety ...
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10/26/2017
From Distance Correlation to Multiscale Generalized Correlation
Understanding and developing a correlation measure that can detect gener...
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09/16/2016
Discovering Relationships and their Structures Across Disparate Data Modalities
Determining whether certain properties are related to other properties i...
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02/04/2015
Sparse Representation Classification Beyond L1 Minimization and the Subspace Assumption
The sparse representation classifier (SRC) proposed in Wright et al. (20...
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12/12/2014
Manifold Matching using Shortest-Path Distance and Joint Neighborhood Selection
Matching datasets of multiple modalities has become an important task in...
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11/23/2013
Robust Vertex Classification
For random graphs distributed according to stochastic blockmodels, a spe...
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04/30/2013
Generalized Canonical Correlation Analysis for Classification
For multiple multivariate data sets, we derive conditions under which Ge...
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01/09/2013
