AIMC Topic: Stochastic Processes

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Comparing Deterministic and Stochastic Reinforcement Learning for Glucose Regulation in Type 1 Diabetes.

Studies in health technology and informatics Aug 7, 2025
Type 1 Diabetes (T1D) is a chronic condition affecting millions worldwide, requiring external insulin administration to regulate blood glucose levels and prevent serious complications. Artificial Pancreas Systems (APS) for managing T1D currently rely...
Adolescent Blood Glucose Computer Simulation Adult Stochastic Processes Reinforcement, Psychology Pancreas, Artificial Insulin Diabetes Mellitus, Type 1 Humans Machine Learning Algorithms
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Air quality monitoring and mitigation through time series forecasting and stochastic optimization.

Journal of environmental management Aug 1, 2025
Poor air quality poses significant threats to public health and environmental sustainability. To mitigate such risks, accurate air quality prediction is essential to inform intervention policies that effectively reduce pollutant levels. While past re...
Forecasting Ontario Machine Learning Stochastic Processes Air Pollution Particulate Matter Environmental Monitoring Air Pollutants
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A novel intelligent framework for assessing within-host transmission dynamics of Chikungunya virus using an unsupervised stochastic neural network approach.

Computational biology and chemistry Aug 1, 2025
In this study, we present a novel intelligent computing framework based on unsupervised random projection neural networks for analyzing the within-host transmission dynamics of the Chikungunya virus with an adaptive immune response. In addition to th...
Stochastic Processes Chikungunya virus Humans Chikungunya Fever Neural Networks, Computer
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Exponential stability of infinite-dimensional impulsive stochastic systems with Poisson jumps under aperiodically intermittent control.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
This paper studies the problem of mean square exponential stability (ES) for a class of impulsive stochastic infinite-dimensional systems with Poisson jumps (ISIDSP) using aperiodically intermittent control (AIC). It provides a detailed analysis of i...
Stochastic Processes Computer Simulation Poisson Distribution Neural Networks, Computer Algorithms
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StoCFL: A stochastically clustered federated learning framework for Non-IID data with dynamic client participation.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices. In real-world federated learning systems, these data samples are often decentralized and Non-Independently Identically Dist...
Neural Networks, Computer Machine Learning Algorithms Cluster Analysis Humans Stochastic Processes Federated Learning
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Elucidating the Theoretical Underpinnings of Surrogate Gradient Learning in Spiking Neural Networks.

Neural computation Apr 17, 2025
Training spiking neural networks to approximate universal functions is essential for studying information processing in the brain and for neuromorphic computing. Yet the binary nature of spikes poses a challenge for direct gradient-based training. Su...
Neurons Stochastic Processes Neural Networks, Computer Learning Models, Neurological Action Potentials Humans
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Asymptotic expansions as control variates for deep solvers to fully-coupled forward-backward stochastic differential equations.

PloS one Jan 1, 2025
Coupled forward-backward stochastic differential equations (FBSDEs) are closely related to financially important issues such as optimal investment. However, it is well known that obtaining solutions is challenging, even when employing numerical metho...
Neural Networks, Computer Algorithms Stochastic Processes
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Deep STI: Deep Stochastic Time-series Imputation on Electronic Health Records.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Electronic Health Records (EHRs) are a cornerstone of modern healthcare analytics, offering rich datasets for various disease analyses through advanced deep learning algorithms. However, the pervasive issue of missing values in EHRs significantly ham...
Humans Deep Learning Time Factors Stochastic Processes Algorithms Liver Neoplasms Electronic Health Records Taiwan
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Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes.

Neural computation Jun 7, 2024
In recent years, there has been an intense debate about how learning in biological neural networks (BNNs) differs from learning in artificial neural networks. It is often argued that the updating of connections in the brain relies only on local infor...
Stochastic Processes Neural Networks, Computer Deep Learning Supervised Machine Learning Models, Neurological Nerve Net
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SEINN: A deep learning algorithm for the stochastic epidemic model.

Mathematical biosciences and engineering : MBE Aug 14, 2023
Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamical system. Stochastic models are deemed more appropriate than deterministic models accounting in terms of essential and practical information about a ...
Stochastic Processes Deep Learning Neural Networks, Computer Nonlinear Dynamics Algorithms
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