activity
20172026
most citedSemiparametric spectral modeling of the Drosophila connectome

23 citations · 23 across the 10 of their papers we have counts for

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5 papers · 1 filter

stat.ME2026

Recovering manifold structure in LLM responses through a joint Euclidean mirror

Maximilian Baum, Aranyak Acharyya, Tianyi Chen +5

Understanding the behavior of black-box large language models and determining effective means of comparing their performance is a key task in modern machine learning. We consider h…

stat.ME2025

Multi-rank Subspace Change-point Detection with Application in Monitoring Robotic Swarms

Jonghyeok Lee, Yao Xie, Youngser Park +3

We study real-time detection of low-rank changes in the covariance structure of high-dimensional streaming data, motivated by robotic swarm monitoring. Building on the spiked covar…

stat.ME2024

Consistent response prediction for multilayer networks on unknown manifolds

Aranyak Acharyya, Jesús Arroyo Relión, Michael Clayton +3

Our paper deals with a collection of networks on a common set of nodes, where some of the networks are associated with responses. Assuming that the networks correspond to points on…

stat.ME2024

Euclidean mirrors and first-order changepoints in network time series

Tianyi Chen, Zachary Lubberts, Avanti Athreya +2

We describe a model for a network time series whose evolution is governed by an underlying stochastic process, known as the latent position process, in which network evolution can…

stat.ME2018

On estimation and inference in latent structure random graphs

Avanti Athreya, Minh Tang, Youngser Park +1

We define a latent structure model (LSM) random graph as a random dot product graph (RDPG) in which the latent position distribution incorporates both probabilistic and geometric c…