Neural networks : the official journal of the International Neural Network Society
May 14, 2021
Robustness of deep neural networks is a critical issue in practical applications. In the general case of feed-forward neural networks (including convolutional deep neural network architectures), under random noise attacks, we propose to study the pro...
Neural networks : the official journal of the International Neural Network Society
Apr 8, 2021
This paper presents new theoretical results on the multi-periodicity of recurrent neural networks with time delays evoked by periodic inputs under stochastic disturbances and state-dependent switching. Based on the geometric properties of activation ...
International journal of occupational safety and ergonomics : JOSE
Mar 19, 2021
. A necessity for this study was felt in the catalyst replacement process as a maintenance operation, because some fatal incidents have occurred due to human error in process industries during catalyst replacement operation. Identification and evalua...
Deep learning models based on medical images play an increasingly important role for cancer outcome prediction. The standard approach involves usage of convolutional neural networks (CNNs) to automatically extract relevant features from the patient's...
Neural networks : the official journal of the International Neural Network Society
Mar 5, 2021
In regression analysis under artificial neural networks, the prediction performance depends on determining the appropriate weights between layers. As randomly initialized weights are updated during back-propagation using the gradient descent procedur...
Early childhood asthma diagnosis is common; however, many children diagnosed before age 5 experience symptom resolution and it remains difficult to identify individuals whose symptoms will persist. Our objective was to develop machine learning models...
Statistical phylogenetic analysis currently relies on complex, dedicated software packages, making it difficult for evolutionary biologists to explore new models and inference strategies. Recent years have seen more generic solutions based on probabi...
Neural networks : the official journal of the International Neural Network Society
Feb 23, 2021
We derive the fast convergence rates of a deep neural network (DNN) classifier with the rectified linear unit (ReLU) activation function learned using the hinge loss. We consider three cases for a true model: (1) a smooth decision boundary, (2) smoot...
We describe a novel approach to estimating the predictability of utterances given extralinguistic context in psycholinguistic research. Predictability effects on language production and comprehension are widely attested, but so far predictability has...
Despite having a similar post-operative complication profile, cardiac valve operations are associated with a higher mortality rate compared to coronary artery bypass grafting (CABG) operations. For long-term mortality, few predictors are known. In th...
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