AIMC Topic: Computer Simulation

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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
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...

Efficient and scalable prediction of stochastic reaction-diffusion processes using graph neural networks.

Mathematical biosciences
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 ...

A Human-Machine Agent Based on Active Reinforcement Learning for Target Classification in Wargame.

IEEE transactions on neural networks and learning systems
To meet the requirements of high accuracy and low cost of target classification in modern warfare, and lay the foundation for target threat assessment, the article proposes a human-machine agent for target classification based on active reinforcement...

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

PloS one
To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the...

A computationally efficient and robust looming perception model based on dynamic neural field.

Neural networks : the official journal of the International Neural Network Society
There are primarily two classes of bio-inspired looming perception visual systems. The first class employs hierarchical neural networks inspired by well-acknowledged anatomical pathways responsible for looming perception, and the second maps nonlinea...

Mittag-Leffler stability and application of delayed fractional-order competitive neural networks.

Neural networks : the official journal of the International Neural Network Society
In the article, the Mittag-Leffler stability and application of delayed fractional-order competitive neural networks (FOCNNs) are developed. By virtue of the operator pair, the conditions of the coexistence of equilibrium points (EPs) are discussed a...

Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning.

Journal of chemical information and modeling
Foods possess a range of unexplored functionalities; however, fully identifying these functions through empirical means presents significant challenges. In this study, we have proposed an approach to comprehensively predict the functionalities of fo...

Step into the era of large multimodal models: a pilot study on ChatGPT-4V(ision)'s ability to interpret radiological images.

International journal of surgery (London, England)
BACKGROUND: The introduction of ChatGPT-4V's 'Chat with images' feature represents the beginning of the era of large multimodal models (LMMs), which allows ChatGPT to process and answer questions based on uploaded images. This advancement has the pot...

pyDarwin machine learning algorithms application and comparison in nonlinear mixed-effect model selection and optimization.

Journal of pharmacokinetics and pharmacodynamics
Forward addition/backward elimination (FABE) has been the standard for population pharmacokinetic model selection (PPK) since NONMEM® was introduced. We investigated five machine learning (ML) algorithms (Genetic algorithm [GA], Gaussian process [GP]...

Unified analysis on multistablity of fraction-order multidimensional-valued memristive neural networks.

Neural networks : the official journal of the International Neural Network Society
This article provides a unified analysis of the multistability of fraction-order multidimensional-valued memristive neural networks (FOMVMNNs) with unbounded time-varying delays. Firstly, based on the knowledge of fractional differentiation and memri...