
Multiple Network Embedding for Anomaly Detection in Time Series of Graphs
This paper considers the graph signal processing problem of anomaly dete...
read it

Robust Similarity and Distance Learning via Decision Forests
Canonical distances such as Euclidean distance often fail to capture the...
read it

Statistical Analysis of Data Repeatability Measures
The advent of modern data collection and processing techniques has seen ...
read it

mvlearn: Multiview Machine Learning in Python
As data are generated more and more from multiple disparate sources, mul...
read it

Learning to rank via combining representations
Learning to rank – producing a ranked list of items specific to a query ...
read it

A New Age of Computing and the Brain
The history of computer science and brain sciences are intertwined. In h...
read it

A general approach to progressive intelligence
In biological learning, data is used to improve performance on the task ...
read it

A general approach to progressive learning
In biological learning, data is used to improve performance on the task ...
read it

The ChiSquare Test of Distance Correlation
Distance correlation has gained much recent attention in the statistics ...
read it

Improving Power of 2Sample Random Graph Tests with Applications in Connectomics
In many applications, there is an interest in testing whether two graphs...
read it

The Exact Equivalence of Independence Testing and TwoSample Testing
Testing independence and testing equality of distributions are two tight...
read it

Manifold Forests: Closing the Gap on Neural Networks
Decision forests (DF), in particular random forests and gradient boostin...
read it

AutoGMM: Automatic Gaussian Mixture Modeling in Python
Gaussian mixture modeling is a fundamental tool in clustering, as well a...
read it

Graphyti: A SemiExternal Memory Graph Library for FlashGraph
Graph datasets exceed the inmemory capacity of most standalone machines...
read it

Geodesic Learning via Unsupervised Decision Forests
Geodesic distance is the shortest path between two points in a Riemannia...
read it

hyppo: A Comprehensive Multivariate Hypothesis Testing Python Package
We introduce hyppo, a unified library for performing multivariate hypoth...
read it

mgcpy: A Comprehensive High Dimensional Independence Testing Python Package
With the increase in the amount of data in many fields, a method to cons...
read it

Inference for multiple heterogeneous networks with a common invariant subspace
The development of models for multiple heterogeneous network data is of ...
read it

Graph Independence Testing
Identifying statistically significant dependency between variables is a ...
read it

clusterNOR: A NUMAOptimized Clustering Framework
Clustering algorithms are iterative and have complex data access pattern...
read it

Decision Forests Induce Characteristic Kernels
Decision forests are popular tools for classification and regression. Th...
read it

On a 'Two Truths' Phenomenon in Spectral Graph Clustering
Clustering is concerned with coherently grouping observations without an...
read it

Forest Packing: Fast, Parallel Decision Forests
Machine learning has an emerging critical role in highperformance compu...
read it

The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing
Distancebased methods, also called "energy statistics", are leading met...
read it

Signal Subgraph Estimation Via Vertex Screening
Graph classification and regression have wide applications in a variety ...
read it

Energy Clustering
Energy statistics was proposed by Székely in the 80's inspired by the Ne...
read it

From Distance Correlation to Multiscale Generalized Correlation
Understanding and developing a correlation measure that can detect gener...
read it

Statistical inference on random dot product graphs: a survey
The random dot product graph (RDPG) is an independentedge random graph ...
read it

Linear Optimal Low Rank Projection for HighDimensional MultiClass Data
Classification of individual samples into one or more categories is crit...
read it

Semiparametric spectral modeling of the Drosophila connectome
We present semiparametric spectral modeling of the complete larval Droso...
read it

Joint Embedding of Graphs
Feature extraction and dimension reduction for networks is critical in a...
read it

A Large Deformation Diffeomorphic Approach to Registration of CLARITY Images via Mutual Information
CLARITY is a method for converting biological tissues into translucent a...
read it

Probabilistic FluorescenceBased Synapse Detection
Brain function results from communication between neurons connected by c...
read it

Discovering Relationships and their Structures Across Disparate Data Modalities
Determining whether certain properties are related to other properties i...
read it

Law of Large Graphs
Estimating the mean of a population of graphs based on a sample is a cor...
read it

Quantifying mesoscale neuroanatomy using Xray microtomography
Methods for resolving the 3D microstructure of the brain typically start...
read it

Randomer Forests
Random forests (RF) is a popular general purpose classifier that has bee...
read it

Manifold Matching using ShortestPath Distance and Joint Neighborhood Selection
Matching datasets of multiple modalities has become an important task in...
read it

An Automated ImagestoGraphs Framework for High Resolution Connectomics
Reconstructing a map of neuronal connectivity is a critical challenge in...
read it

Covariateassisted spectral clustering
Biological and social systems consist of myriad interacting units. The i...
read it

Graph Matching: Relax at Your Own Risk
Graph matchingaligning a pair of graphs to minimize their edge disagr...
read it

Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes
In this paper, we present a new pipeline which automatically identifies ...
read it

Seeded Graph Matching Via Joint Optimization of Fidelity and Commensurability
We present a novel approximate graph matching algorithm that incorporate...
read it

Spectral Clustering for DivideandConquer Graph Matching
We present a parallelized bijective graph matching algorithm that levera...
read it

Bayesian crack detection in ultra high resolution multimodal images of paintings
The preservation of our cultural heritage is of paramount importance. Th...
read it

Statistical inference on errorfully observed graphs
Statistical inference on graphs is a burgeoning field in the applied and...
read it
Joshua T. Vogelstein
verfied profile
Assistant Professor Dept. of Biomedical Engineering at Johns Hopkins University