AIMC Topic: Probability

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Probability-Based Early Warning for Seasonal Influenza in China: Model Development Study.

JMIR medical informatics Aug 6, 2025
BACKGROUND: Seasonal influenza is a major global public health concern, leading to escalated morbidity and mortality rates. Traditional early warning models rely on binary (0/1) classification methods, which issue alerts only when predefined threshol...
Humans Machine Learning Influenza, Human Seasons Probability Risk Assessment China
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Kernel-free quadratic surface SVM for conditional probability estimation in imbalanced multi-class classification.

Neural networks : the official journal of the International Neural Network Society Apr 25, 2025
For the multi-class classification problems, we propose a new probabilistic output classifier called kernel-free quadratic surface support vector machine for conditional probability estimation (CPSQSVM), which is based on a newly developed binary cla...
Support Vector Machine Algorithms Probability
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Multi-Granularity Autoformer for long-term deterministic and probabilistic power load forecasting.

Neural networks : the official journal of the International Neural Network Society Apr 24, 2025
Long-term power load forecasting is critical for power system planning but is constrained by intricate temporal patterns. Transformer-based models emphasize modeling long- and short-term dependencies yet encounter limitations from complexity and para...
Electric Power Supplies Uncertainty Humans Neural Networks, Computer Models, Statistical Forecasting Probability
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Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

Journal of environmental management Mar 24, 2025
For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be processed from point inventories to surface predictive maps. For large-scale predictive mapping, very fe...
Machine Learning Soil Environmental Monitoring Soil Pollutants Probability Farms Agriculture Czech Republic
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Deep one-class probability learning for end-to-end image classification.

Neural networks : the official journal of the International Neural Network Society Jan 27, 2025
One-class learning has many application potentials in novelty, anomaly, and outlier detection systems. It aims to distinguish both positive and negative samples with a model trained via only positive samples or one-class annotated samples. With the d...
Probability Probability Learning Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans
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CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks.

Neural networks : the official journal of the International Neural Network Society Jan 27, 2025
Effective uncertainty estimation is becoming increasingly attractive for enhancing the reliability of neural networks. This work presents a novel approach, termed Credal-Set Interval Neural Networks (CreINNs), for classification. CreINNs retain the f...
Probability Uncertainty Humans Neural Networks, Computer Algorithms Bayes Theorem
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On the probability of necessity and sufficiency of explaining Graph Neural Networks: A lower bound optimization approach.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2024
The explainability of Graph Neural Networks (GNNs) is critical to various GNN applications, yet it remains a significant challenge. A convincing explanation should be both necessary and sufficient simultaneously. However, existing GNN explaining appr...
Graph Neural Networks Algorithms Probability Humans Neural Networks, Computer
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Probabilistic-sampling-based asynchronous control for semi-Markov jumping neural networks with reaction-diffusion terms.

Neural networks : the official journal of the International Neural Network Society Dec 24, 2024
This paper investigates the probabilistic-sampling-based asynchronous control problem for semi-Markov reaction-diffusion neural networks (SMRDNNs). Aiming at mitigating the drawback of the well-known fixed-sampling control law, a more general probabi...
Stochastic Processes Neural Networks, Computer Probability Algorithms Markov Chains Computer Simulation
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Unifying invariant and variant features for graph out-of-distribution via probability of necessity and sufficiency.

Neural networks : the official journal of the International Neural Network Society Dec 20, 2024
Graph Out-of-Distribution (OOD), requiring that models trained on biased data generalize to the unseen test data, has considerable real-world applications. One of the most mainstream methods is to extract the invariant subgraph by aligning the origin...
Humans Algorithms Neural Networks, Computer Machine Learning Probability
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A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults.

Computers, informatics, nursing : CIN Dec 1, 2024
Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction model to predict the fall risk category among community-dwelling older adults, leading to earlier i...
Aged, 80 and over Male Humans Risk Assessment China Risk Factors Aged Machine Learning Probability East Asian People Female Independent Living Bayes Theorem Accidental Falls Logistic Models
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