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Computer Simulation

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Bias-reduced neural networks for parameter estimation in quantitative MRI.

Magnetic resonance in medicine
PURPOSE: To develop neural network (NN)-based quantitative MRI parameter estimators with minimal bias and a variance close to the Cramér-Rao bound.

Distributed adaptive robust containment control for reaction-diffusion neural networks with external disturbances under directed graphs.

Neural networks : the official journal of the International Neural Network Society
In this paper, the leader-follower robust synchronization issue is mainly addressed for reaction-diffusion neural networks (RDNNs) with multiple leaders and external disturbances under directed graphs. Based on the σ modification approach, we propose...

Agent-based approaches for biological modeling in oncology: A literature review.

Artificial intelligence in medicine
CONTEXT: Computational modeling involves the use of computer simulations and models to study and understand real-world phenomena. Its application is particularly relevant in the study of potential interactions between biological elements. It is a pro...

LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data.

Neural networks : the official journal of the International Neural Network Society
Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential equations (PDE). However, it requires a large amo...

Automatic Vehicle Fueling System using PLC Controlled Robotic Arm - A Simulation Design.

F1000Research
The objective of this research is to simulate an automatic fuelling system using a PLC LogixPro simulation. The system includes the "FASS" concept, which is Fast, Accurate, Safe and Simple, to allow car users to have an efficient fuel filling system....

Learning spatio-temporal patterns with Neural Cellular Automata.

PLoS computational biology
Neural Cellular Automata (NCA) are a powerful combination of machine learning and mechanistic modelling. We train NCA to learn complex dynamics from time series of images and Partial Differential Equation (PDE) trajectories. Our method is designed to...

Towards complex dynamic physics system simulation with graph neural ordinary equations.

Neural networks : the official journal of the International Neural Network Society
The great learning ability of deep learning facilitates us to comprehend the real physical world, making learning to simulate complicated particle systems a promising endeavour both in academia and industry. However, the complex laws of the physical ...

[The revolution of AI in drug development].

Medecine sciences : M/S
Artificial intelligence and machine learning enable the construction of predictive models, which are currently used to assist in decision-making throughout the process of drug discovery and development. These computational models can be used to repre...

The role of directed cycles in a directed neural network.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the dynamics of a directed acyclic neural network by edge adding control. We find that the local stability and Hopf bifurcation of the controlled network only depend on the size and intersection of directed cycles, instead of ...

Adversarial AI applied to cross-user inter-domain and intra-domain adaptation in human activity recognition using wireless signals.

PloS one
In recent years, researchers have successfully recognised human activities using commercially available WiFi (Wireless Fidelity) devices. The channel state information (CSI) can be gathered at the access point with the help of a network interface con...