Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning [2] Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a ...

In this paper, we propose a method for explaining the working mechanism of deep-learning-based traffic classification as a method of XAI based on a genetic algorithm. We describe the mechanism of the ...

Unofficial implementation of the paper Evolutionary design of molecules based on deep learning and a genetic algorithm. There are a few improvements ... (2) Latent space will be using independent ...

We conclude that the wide generic capacities and modularity of deep neural networks allow them to be customized easily to learn the deciphering task of the genetic code efficiently. We meant to show ...

Thus, in this paper, we propose an algorithm called Deep Learning Trained by Genetic Algorithm (DL-GA), which combines the advantages of DL and GA. GA will collect states and paths from various ...

With all the excitement over neural networks and deep-learning ... for Cartesian genetic programming (as their technique is called). The process begins by randomly creating a code containing ...

Deep artificial neural networks (DNNs) are typically trained via gradient-based learning ... algorithms can work at DNN scales. Here we demonstrate they can: we evolve the weights of a DNN with a ...

Researchers have successfully employed an algorithm to identify potential ... identifies "open" regions of the genome, and PRINT, a deep-learning-based method to detect these types of footprints ...

Deep learning algorithms ... not code for proteins seemed to be implicated in these disorders at higher frequency, which means they may serve as alternative markers. "By identifying genetic ...

In this work, we develop a deep learning framework to generate collagen sequences ... desired thermal stability for biomedical applications. The machine learning–based genetic algorithm used. Three ...