Publications associées à Processus stochastique

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

In this article, we study the problem of Byzantine fault-tolerance in a federated optimization setting, where there is a group of agents communicating with a centralized coordinator. We allow up to

f

Byzantine-faulty agents, which may not follow a prescr ...

Piscataway2023

Autocatalysis and CO2: Carbon Capture and Utilization (CCU) Meets Natural Processes

Paul Joseph Dyson, Jorge Gustavo Uranga, Martin Hulla, Gabriela Gastelu

Autocatalytic reactions were proposed to play a key role at the beginning of life starting from the first reduction of CO2 to formate, acetate and C-1-C-4 hydrocarbons. In carbon capture and utilization (CCU) processes, the same reactions were demonstrated ...

Weinheim2023

Lp-regularity theory for the stochastic reaction-diffusion equation with super-linear multiplicative noise and strong dissipativity

Jaeyun Yi

We study the existence, uniqueness, and regularity of the solution to the stochastic reaction-diffusion equation (SRDE) with colored noise F-center dot:partial derivative(t)u = aijuxixj +biuxi + cu - bu1+beta +xi u1+gamma F-center dot, (t, x) is ...

San Diego2023

Stochastic Models for Comparison-based Search

Daniyar Chumbalov

In this thesis we study a problem of searching in a space of objects using comparisons. To navigate through the space to the target object

t

, we ask a sequence of questions of the form ``which object

i

or

j

is closer to

t

?'' for which we observe no ...

EPFL2023

Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings

Fabio Nobile, Juan Pablo Madrigal Cianci

In this work, we present, analyze, and implement a class of multilevel Markov chain Monte Carlo(ML-MCMC) algorithms based on independent Metropolis--Hastings proposals for Bayesian inverse problems. In this context, the likelihood function involves solving ...

2023

On a Finite-Size Neuronal Population Equation

Tilo Schwalger, Valentin Marc Schmutz, Eva Löcherbach

Population equations for infinitely large networks of spiking neurons have a long tradition in theoret-ical neuroscience. In this work, we analyze a recent generalization of these equations to populations of finite size, which takes the form of a nonlinear ...

SIAM PUBLICATIONS2023

Millimeter-wave to near-terahertz sensors based on reversible insulator-to-metal transition in VO2

Mihai Adrian Ionescu, Teodor Rosca, Fatemeh Qaderi Rahaqi

In the quest for low power bio-inspired spiking sensors, functional oxides like vanadium dioxide are expected to enable future energy efficient sensing. Here, we report uncooled millimeter-wave spiking detectors based on the sensitivity of insulator-to-met ...

SPRINGERNATURE2023

Tensor approximation of the self-diffusion matrix of tagged particle processes

Christoph Max Strössner

The objective of this paper is to investigate a new numerical method for the approximation of the self-diffusion matrix of a tagged particle process defined on a grid. While standard numerical methods make use of long-time averages of empirical means of de ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Low-Rank Tensor Methods for High-Dimensional Problems

Christoph Max Strössner

In this thesis, we propose and analyze novel numerical algorithms for solving three different high-dimensional problems involving tensors. The commonality of these problems is that the tensors can potentially be well approximated in low-rank formats. Ident ...

EPFL2023

Kinetic Network Modeling of the Catalytic Upgrading of Biomass's Acetate Fraction to Aromatics

Jeremy Luterbacher, Jher Hau Yeap, Bartosz Rozmyslowicz, Ahmed Mohamed Ibrahim Elkhaiary

The acetate fraction is the fourth most abundant fraction by weight in many plant species and can be easily extracted as acetic acid in high yields. We have previously shown that acetic acid obtained from steam pretreated beech wood could be upgraded in a ...

Washington2023

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Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Autocatalysis and CO2: Carbon Capture and Utilization (CCU) Meets Natural Processes

Lp-regularity theory for the stochastic reaction-diffusion equation with super-linear multiplicative noise and strong dissipativity

Stochastic Models for Comparison-based Search

Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings

On a Finite-Size Neuronal Population Equation

Millimeter-wave to near-terahertz sensors based on reversible insulator-to-metal transition in VO2

Tensor approximation of the self-diffusion matrix of tagged particle processes

Low-Rank Tensor Methods for High-Dimensional Problems

Kinetic Network Modeling of the Catalytic Upgrading of Biomass's Acetate Fraction to Aromatics

On a Finite-Size Neuronal Population Equation

Low-Rank Tensor Methods for High-Dimensional Problems

Kinetic Network Modeling of the Catalytic Upgrading of Biomass's Acetate Fraction to Aromatics

Autocatalysis and CO2: Carbon Capture and Utilization (CCU) Meets Natural Processes

Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Tensor approximation of the self-diffusion matrix of tagged particle processes

Lp-regularity theory for the stochastic reaction-diffusion equation with super-linear multiplicative noise and strong dissipativity

Stochastic Models for Comparison-based Search

Millimeter-wave to near-terahertz sensors based on reversible insulator-to-metal transition in VO2