AIMC Topic: Stochastic Processes

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Using recurrent neural network to estimate irreducible stochasticity in human choice behavior.

eLife Sep 6, 2024
Theoretical computational models are widely used to describe latent cognitive processes. However, these models do not equally explain data across participants, with some individuals showing a bigger predictive gap than others. In the current study, w...
Neural Networks, Computer Computer Simulation Female Humans Reinforcement, Psychology Choice Behavior Male Decision Making Stochastic Processes Young Adult Adult
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Timely ICU Outcome Prediction Utilizing Stochastic Signal Analysis and Machine Learning Techniques with Readily Available Vital Sign Data.

IEEE journal of biomedical and health informatics Sep 5, 2024
The ICU is a specialized hospital department that offers critical care to patients at high risk. The massive burden of ICU-requiring care requires accurate and timely ICU outcome predictions for alleviating the economic and healthcare burdens imposed...
Aged Adult Male Intensive Care Units Female Humans Critical Care Vital Signs Middle Aged Machine Learning Stochastic Processes Algorithms Deep Learning Prognosis Signal Processing, Computer-Assisted
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StochCA: A novel approach for exploiting pretrained models with cross-attention.

Neural networks : the official journal of the International Neural Network Society Aug 23, 2024
Utilizing large-scale pretrained models is a well-known strategy to enhance performance on various target tasks. It is typically achieved through fine-tuning pretrained models on target tasks. However, naï ve fine-tuning may not fully leverage knowle...
Neural Networks, Computer Machine Learning Algorithms Humans Stochastic Processes Transfer, Psychology
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Protocol-based control for semi-Markov reaction-diffusion neural networks.

Neural networks : the official journal of the International Neural Network Society Jul 22, 2024
This paper addresses the asynchronous control problem for semi-Markov reaction-diffusion neural networks (SMRDNNs) under probabilistic event-triggered protocol (PETP) scheduling. A semi-Markov process with a deterministic switching rule is introduced...
Stochastic Processes Computer Simulation Neural Networks, Computer Probability Algorithms Markov Chains
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Groundwater health risk assessment and its temporal and spatial evolution based on trapezoidal fuzzy number-Monte Carlo stochastic simulation: A case study in western Jilin province.

Ecotoxicology and environmental safety Jul 17, 2024
The United States Environmental Protection Agency (USEPA) Four-step-Method (FSM) is a straightforward and extensively utilized tool for evaluating regional health risks, However, the complex and heterogeneous groundwater environment system causes gre...
Humans China Monte Carlo Method Groundwater Risk Assessment Stochastic Processes Water Pollutants, Chemical Environmental Monitoring Spatio-Temporal Analysis Fuzzy Logic Uncertainty Water Quality
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T-distributed Stochastic Neighbor Network for unsupervised representation learning.

Neural networks : the official journal of the International Neural Network Society Jul 9, 2024
Unsupervised representation learning (URL) is still lack of a reasonable operator (e.g. convolution kernel) for exploring meaningful structural information from generic data including vector, image and tabular data. In this paper, we propose a simple...
Unsupervised Machine Learning Stochastic Processes Algorithms Single-Cell Analysis Cluster Analysis Humans Neural Networks, Computer
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Unsupervised stochastic learning and reduced order modeling for global sensitivity analysis in cardiac electrophysiology models.

Computer methods and programs in biomedicine Jul 8, 2024
BACKGROUND AND OBJECTIVE: Numerical simulations in electrocardiology are often affected by various uncertainties inherited from the lack of precise knowledge regarding input values including those related to the cardiac cell model, domain geometry, a...
Heart Stochastic Processes Models, Cardiovascular Uncertainty Electrophysiological Phenomena Algorithms Computer Simulation Humans Unsupervised Machine Learning
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Efficient and scalable prediction of stochastic reaction-diffusion processes using graph neural networks.

Mathematical biosciences Jul 8, 2024
The dynamics of locally interacting particles that are distributed in space give rise to a multitude of complex behaviours. However the simulation of reaction-diffusion processes which model such systems is highly computationally expensive, the cost ...
Stochastic Processes Neural Networks, Computer Computer Simulation Models, Biological Monte Carlo Method
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Facial micro-expression recognition using stochastic graph convolutional network and dual transferred learning.

Neural networks : the official journal of the International Neural Network Society Jun 3, 2024
Micro-expression recognition (MER) has drawn increasing attention due to its wide application in lie detection, criminal detection and psychological consultation. However, the best recognition accuracy on recent public dataset is still low compared t...
Humans Machine Learning Algorithms Neural Networks, Computer Image Processing, Computer-Assisted Automated Facial Recognition Facial Expression Stochastic Processes
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Robust Stochastic Neural Ensemble Learning With Noisy Labels for Thoracic Disease Classification.

IEEE transactions on medical imaging Jun 3, 2024
Chest radiography is the most common radiology examination for thoracic disease diagnosis, such as pneumonia. A tremendous number of chest X-rays prompt data-driven deep learning models in constructing computer-aided diagnosis systems for thoracic di...
Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Databases, Factual Thoracic Diseases Stochastic Processes Humans Neural Networks, Computer Deep Learning Algorithms
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