AIMC Topic: Computer Simulation

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SympGNNs: Symplectic Graph Neural Networks for identifying high-dimensional Hamiltonian systems and node classification.

Neural networks : the official journal of the International Neural Network Society
Existing neural network models to learn Hamiltonian systems, such as SympNets, although accurate in low-dimensions, struggle to learn the correct dynamics for high-dimensional many-body systems. Herein, we introduce Symplectic Graph Neural Networks (...

Event-based distributed cooperative neural learning control for nonlinear multiagent systems with time-varying output constraints.

Neural networks : the official journal of the International Neural Network Society
In practical engineering, many systems are required to operate under different constraint conditions due to considerations of system security. Violating these constraints conditions during operation may lead to performance degradation. Additionally, ...

A novel one-layer neural network for solving quadratic programming problems.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a novel one-layer neural network to solve quadratic programming problems in real time by using a control parameter and transforming the optimality conditions into a system of projection equations. The proposed network includes two...

EBM-WGF: Training energy-based models with Wasserstein gradient flow.

Neural networks : the official journal of the International Neural Network Society
Energy-based models (EBMs) show their efficiency in density estimation. However, MCMC sampling in traditional EBMs suffers from expensive computation. Although EBMs with minimax game avoid the above drawback, the energy estimation and generator's opt...

Turbulence control in memristive neural network via adaptive magnetic flux based on DLS-ADMM technique.

Neural networks : the official journal of the International Neural Network Society
High-voltage defibrillation for eliminating cardiac spiral waves has significant side effects, necessitating the pursuit of low-energy alternatives for a long time. Adaptive optimization techniques and machine learning methods provide promising solut...

Exponential stability of infinite-dimensional impulsive stochastic systems with Poisson jumps under aperiodically intermittent control.

Neural networks : the official journal of the International Neural Network Society
This paper studies the problem of mean square exponential stability (ES) for a class of impulsive stochastic infinite-dimensional systems with Poisson jumps (ISIDSP) using aperiodically intermittent control (AIC). It provides a detailed analysis of i...

Virtual Cell Challenge: Toward a Turing test for the virtual cell.

Cell
Virtual cells are an emerging frontier at the intersection of artificial intelligence and biology. A key goal of these cell state models is predicting cellular responses to perturbations. The Virtual Cell Challenge is being established to catalyze pr...

Exploring nanoparticles in lungs under COPD conditions for nanospray drug flow and deposition: CFD simulations and AI predictions.

International journal of pharmaceutics
Chronic obstructive pulmonary disease (COPD) plays a heavy burden on individuals and the social health system, not only causing direct medical costs but also economic losses. Today, treatments for COPD include drugs, bronchodilators, and oxygen thera...

Hyperparameter Control Using Fuzzy Logic: Evolving Policies for Adaptive Fuzzy Particle Swarm Optimization Algorithm.

Evolutionary computation
Heuristic optimization methods such as particle swarm optimization (PSO) depend on their parameters to achieve optimal performance on a given class of problems. Some modifications of heuristic algorithms aim at adapting those parameters during the op...