118 citations · 438 across the 49 of their papers we have counts for
61 papers
Hierarchical excitatory processes for modelling event-time data in the presence of exogenous stimuli
Francesco Sanna Passino, Nicholas A. Heard, Jeffrey W. Brown +2
We introduce the Hierarchical Excitatory Process (HEP), a flexible point process model for event-time data observed under repeated external stimuli. The proposed framework models t…
Vertex misalignment and changepoint localization in network time series
Tianyi Chen, Mohammad Sharifi Kiasari, Sijing Yu +5
Inference for time series of networks often relies on accurate vertex correspondence between network realizations at different times. In practice, however, such vertex alignments c…
Data Kernel Perspective Space Performance Guarantees for Synthetic Data from Transformer Models
Michael Browder, Kevin Duh, J. David Harris +5
Scarcity of labeled training data remains the long pole in the tent for building performant language technology and generative AI models. Transformer models -- particularly LLMs --…
Matching and mixing: Matchability of graphs under Markovian error
Zhirui Li, Keith D. Levin, Zhiang Zhao +1
We consider the problem of graph matching for a sequence of graphs generated under a time-dependent Markov chain noise model. Our edgelighter error model, a variant of the classica…
Asymptotically perfect seeded graph matching without edge correlation (and applications to inference)
Tong Qi, Vera Andersson, Peter Viechnicki +1
We present the OmniMatch algorithm for seeded multiple graph matching. In the setting of -dimensional Random Dot Product Graphs (RDPG), we prove that under mild assumptions, Omn…
Gaussian mixture models as a proxy for interacting language models
Edward L. Wang, Mohammad Sharifi Kiasari, Tianyu Wang +4
Large language models (LLMs) are powerful tools that, in a number of settings, overlap with the results of human pattern recognition and reasoning. Retrieval-augmented generation (…