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Probability

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A language modeling-like approach to sketching.

Neural networks : the official journal of the International Neural Network Society
Sketching is a universal communication tool that, despite its simplicity, is able to efficiently express a large variety of concepts and, in some limited contexts, it can be even more immediate and effective than natural language. In this paper we ex...

Establishing a New Link between Fuzzy Logic, Neuroscience, and Quantum Mechanics through Bayesian Probability: Perspectives in Artificial Intelligence and Unconventional Computing.

Molecules (Basel, Switzerland)
Human interaction with the world is dominated by uncertainty. Probability theory is a valuable tool to face such uncertainty. According to the Bayesian definition, probabilities are personal beliefs. Experimental evidence supports the notion that hum...

Confidence-Calibrated Human Activity Recognition.

Sensors (Basel, Switzerland)
Wearable sensors are widely used in activity recognition (AR) tasks with broad applicability in health and well-being, sports, geriatric care, etc. Deep learning (DL) has been at the forefront of progress in activity classification with wearable sens...

Remaining Useful Life Estimation for Engineered Systems Operating under Uncertainty with Causal GraphNets.

Sensors (Basel, Switzerland)
In this work, a novel approach, termed GNN-tCNN, is presented for the construction and training of Remaining Useful Life (RUL) models. The method exploits Graph Neural Networks (GNNs) and deals with the problem of efficiently learning from time serie...

Early Warning of Gas Concentration in Coal Mines Production Based on Probability Density Machine.

Sensors (Basel, Switzerland)
Gas explosion has always been an important factor restricting coal mine production safety. The application of machine learning techniques in coal mine gas concentration prediction and early warning can effectively prevent gas explosion accidents. Nea...

Estimating the conditional probability of developing human papilloma virus related oropharyngeal cancer by combining machine learning and inverse Bayesian modelling.

PLoS computational biology
The epidemic increase in the incidence of Human Papilloma Virus (HPV) related Oropharyngeal Squamous Cell Carcinomas (OPSCCs) in several countries worldwide represents a significant public health concern. Although gender neutral HPV vaccination progr...

Extremely randomized neural networks for constructing prediction intervals.

Neural networks : the official journal of the International Neural Network Society
The aim of this paper is to propose a novel prediction model based on an ensemble of deep neural networks adapting the extremely randomized trees method originally developed for random forests. The extra-randomness introduced in the ensemble reduces ...

A stochastic modeling approach for analyzing water resources systems.

Journal of contaminant hydrology
Many uncertain factors exist in the water resource systems, leading to dynamic characteristics of the water distribution process. Especially for the watershed including irrigation area with multiple water sources and water users, it is complicated th...