PyGAD is an open-source, easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch, and it can optimize both ...

Token optimization is critical for designing precise prompts. A Python framework can be designed to accept an English prompt as input, analyse it, remove duplicate or low-value content, and return a ...

Molecular inverse design is a classically exponential problem that could greatly benefit from quantum computing. Here, we introduce the quantum ensemble variational optimization (QEVO), a quantum ...

Constructing a machine learning model manually involves a long chain of decisions. Many steps are involved, such as cleaning the data, choosing the right algorithm ...

The universal triple-nucleotide genetic code is common to all living organisms on Earth, but it varies in small and subtle ways across the tree of life. Kivenson et al. explored the reassignment of ...

This important study introduces a fully differentiable variant of the Gillespie algorithm as an approximate stochastic simulation scheme for complex chemical reaction networks, allowing kinetic ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. We present an artificial intelligence-guided approach to design durable and chemically ...

Cluster analysis is a popular technique in data analysis and exploration that finds similarities between different groups of data, based on which datasets are classified or segmented into predefined ...