AIMC Topic: Computer Simulation

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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...

Quantifying the biomimicry gap in biohybrid robot-fish pairs.

Bioinspiration & biomimetics
Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from sim...

A novel two-layer fuzzy neural network for solving inequality-constrained ℓ-minimization problem with applications.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a novel two-layer fuzzy neural network model (TLFNN) for solving the inequality-constrained ℓ-minimization problem. The stability and global convergence of the proposed TLFNN model are detailedly analyzed using the Lyapunov ...

A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans.

Pharmaceutical research
PURPOSE: Recently, there has been rapid development in model-informed drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models ...

Towards biologically plausible model-based reinforcement learning in recurrent spiking networks by dreaming new experiences.

Scientific reports
Humans and animals can learn new skills after practicing for a few hours, while current reinforcement learning algorithms require a large amount of data to achieve good performances. Recent model-based approaches show promising results by reducing th...