Avanti Athreya | DeepAI

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Featured Co-authors

Carey E. Priebe
102 publications
Joshua T. Vogelstein
61 publications
Minh Tang
38 publications
Vince Lyzinski
32 publications
Youngser Park
28 publications
Weiwei Yang
20 publications
Daniel L. Sussman
18 publications
Keith Levin
16 publications
Amitabh Basu
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Jonathan Larson
13 publications
Hayden S. Helm
13 publications

∙ 05/13/2022

Discovering underlying dynamics in time series of networks

Understanding dramatic changes in the evolution of networks is central t...

0 Avanti Athreya, et al. ∙

∙ 03/26/2021

Beyond the adjacency matrix: random line graphs and inference for networks with edge attributes

Any modern network inference paradigm must incorporate multiple aspects ...

0 Zachary Lubberts, et al. ∙

∙ 08/23/2020

Multiple Network Embedding for Anomaly Detection in Time Series of Graphs

This paper considers the graph signal processing problem of anomaly dete...

0 Guodong Chen, et al. ∙

∙ 08/01/2020

The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks

Spectral inference on multiple networks is a rapidly-developing subfield...

0 Konstantinos Pantazis, et al. ∙

∙ 07/04/2020

On identifying unobserved heterogeneity in stochastic blockmodel graphs with vertex covariates

Both observed and unobserved vertex heterogeneity can influence block st...

0 Cong Mu, et al. ∙

∙ 05/20/2020

Learning to rank via combining representations

Learning to rank – producing a ranked list of items specific to a query ...

13 Hayden S. Helm, et al. ∙

∙ 02/23/2020

On a complete and sufficient statistic for the correlated Bernoulli random graph model

Inference on vertex-aligned graphs is of wide theoretical and practical ...

0 Donniell E. Fishkind, et al. ∙

∙ 06/24/2019

Inference for multiple heterogeneous networks with a common invariant subspace

The development of models for multiple heterogeneous network data is of ...

0 Jesús Arroyo, et al. ∙

∙ 08/23/2018

On a 'Two Truths' Phenomenon in Spectral Graph Clustering

Clustering is concerned with coherently grouping observations without an...

8 Carey E. Priebe, et al. ∙

∙ 06/04/2018

On estimation and inference in latent structure random graphs

We define a latent structure model (LSM) random graph as a random dot pr...

0 Avanti Athreya, et al. ∙

∙ 09/16/2017

Statistical inference on random dot product graphs: a survey

The random dot product graph (RDPG) is an independent-edge random graph ...

0 Avanti Athreya, et al. ∙

∙ 05/09/2017

Semiparametric spectral modeling of the Drosophila connectome

We present semiparametric spectral modeling of the complete larval Droso...

0 Carey E. Priebe, et al. ∙

∙ 03/07/2015

Community Detection and Classification in Hierarchical Stochastic Blockmodels

We propose a robust, scalable, integrated methodology for community dete...

0 Vince Lyzinski, et al. ∙

∙ 10/02/2013

Perfect Clustering for Stochastic Blockmodel Graphs via Adjacency Spectral Embedding

Vertex clustering in a stochastic blockmodel graph has wide applicabilit...

0 Vince Lyzinski, et al. ∙

∙ 05/31/2013

A central limit theorem for scaled eigenvectors of random dot product graphs

We prove a central limit theorem for the components of the largest eigen...

1 Avanti Athreya, et al. ∙

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