Abstract: The traditional BP neural network exists problems such as easy to fall into local minima during training, slow convergence speed, unstable output, etc. Some scholars optimize it by ...

Abstract: Particle swarm optimization (PSO) motivated by the social behavior of organisms, is a step up to existing evolutionary algorithms for optimization of continuous nonlinear functions.

ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...

where the output is not from a fixed vocabulary, but a sequence of pointers to elements from the input. Main idea: Instead of producing an output token from a fixed-size vocabulary, the model points ...

This repository provides implementation for SNBO (Scalable Neural Network-based Blackbox Optimization) — a novel method for efficient blackbox optimization using neural networks. It also includes code ...

In this paper, we present an innovative approach to accurately extract the device parameters of a semiconductor p-n junction diode using a Multi-Objective Quantum-Inspired Particle Swarm Optimization ...