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From the 1 of 6 linked papers with an AI index.

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20242026
most citedLarge Deviations Analysis for Stochastic Models of Bacterial Evolution

1 citations · 1 across the 2 of their papers we have counts for

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6 papers

math.PR20261 cited

Large Deviations Analysis for Stochastic Models of Bacterial Evolution

Robert Azencott, Brett Geiger, Ilya Timofeyev

The paper develops a large‑deviation framework for discrete‑time Markov chain models of bacterial population genetics, deriving explicit cost functions for histogram dynamics and m…

math.NA2026

Parametric Reduced Order Models for the Generalized Kuramoto--Sivashinsky Equations

Md Rezwan Bin Mizan, Maxim Olshanskii, Ilya Timofeyev

The paper studies parametric Reduced Order Models (ROMs) for the Kuramoto--Sivashinsky (KS) and generalized Kuramoto--Sivashinsky (gKS) equations. We consider several POD and POD-D…

nlin.CD2026

Using Echo-State Networks to Reproduce Rare Events in Chaotic Systems

Anton Erofeev, Balasubramanya T. Nadiga, Ilya Timofeyev

We apply Echo-State Networks to predict time series and statistical properties of the competitive Lotka-Volterra model in the chaotic regime. In particular, we demonstrate that Ech…

math.DS2025

Attractor learning for spatiotemporally chaotic dynamical systems using echo state networks with transfer learning

Mohammad Shah Alam, William Ott, Ilya Timofeyev

In this paper, we explore the predictive capabilities of echo state networks (ESNs) for the generalized Kuramoto-Sivashinsky (gKS) equation, an archetypal nonlinear PDE that exhibi…

physics.comp-ph2025

Application of Machine Learning and Convex Limiting to Subgrid Flux Modeling in the Shallow-Water Equations

Ilya Timofeyev, Alexey Schwarzmann, Dmitri Kuzmin

We propose a combination of machine learning and flux limiting for property-preserving subgrid scale modeling in the context of flux-limited finite volume methods for the one-dimen…

math.PR2024

Modeling Information Flow with a Multi-Stage Queuing Mode

Mohammad Daneshvar, Richard C. Barnard, Cory Hauck +1

In this paper, we introduce a nonlinear stochastic model to describe the propagation of information inside a computer processor. In this model, a computational task is divided into…