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Stochastic Processes

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Paying attention to uncertainty: A stochastic multimodal transformers for post-traumatic stress disorder detection using video.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Post-traumatic stress disorder is a debilitating psychological condition that can manifest following exposure to traumatic events. It affects individuals from diverse backgrounds and is associated with various symptoms, inc...

Forecasting and Predicting Stochastic Agent-Based Model Data with Biologically-Informed Neural Networks.

Bulletin of mathematical biology
Collective migration is an important component of many biological processes, including wound healing, tumorigenesis, and embryo development. Spatial agent-based models (ABMs) are often used to model collective migration, but it is challenging to thor...

Optimization control for mean square synchronization of stochastic semi-Markov jump neural networks with non-fragile hidden information and actuator saturation.

Neural networks : the official journal of the International Neural Network Society
This paper studies the asynchronous output feedback control and H synchronization problems for a class of continuous-time stochastic hidden semi-Markov jump neural networks (SMJNNs) affected by actuator saturation. Initially, a novel neural networks ...

Delayed-feedback oscillators replicate the dynamics of multiplex networks: Wavefront propagation and stochastic resonance.

Neural networks : the official journal of the International Neural Network Society
The widespread development and use of neural networks have significantly enriched a wide range of computer algorithms and promise higher speed at lower cost. However, the imitation of neural networks by means of modern computing substrates is highly ...

Dynamics of infectious disease mathematical model through unsupervised stochastic neural network paradigm.

Computational biology and chemistry
The viruses has spread globally and have been impacted lives of people socially and economically, which causes immense suffering throughout the world. Thousands of people died and millions of illnesses were brought, by the outbreak worldwide. In orde...

Statistical inference and neural network training based on stochastic difference model for air pollution and associated disease transmission.

Journal of theoretical biology
A polluted air environment can potentially provoke infections of diverse respiratory diseases. The development of mathematical models can study the mechanism of air pollution and its effect on the spread of diseases. The key is to characterize the in...

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
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...

Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP.

Neural networks : the official journal of the International Neural Network Society
Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networks with similar learning abilities remains a challenge. In particular, it is unresolved how differen...

Data-dependent stability analysis of adversarial training.

Neural networks : the official journal of the International Neural Network Society
Stability analysis is an essential aspect of studying the generalization ability of deep learning, as it involves deriving generalization bounds for stochastic gradient descent-based training algorithms. Adversarial training is the most widely used d...

Fractional-order stochastic gradient descent method with momentum and energy for deep neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel fractional-order stochastic gradient descent with momentum and energy (FOSGDME) approach is proposed. Specifically, to address the challenge of converging to a real extreme point encountered by the existing fractional gradient ...