Aiming at improving the resolution and accuracy of MDEIT and providing an efficient imaging method for breast cancer diagnosis, a new algorithm based on stacked auto-encoder (SAE) neural network is ...

we propose a novel deep-learning-based algorithm, Moanna, that is trained to integrate multi-omics data for predicting breast cancer subtypes. Moanna’s architecture consists of a semi-supervised ...

This is a simple example of using a neural network as an autoencoder without using any machine learning ... The feedforward and backpropagation algorithm equations, using the sigmoid function as an ...

In this work, we propose an autoencoder (AE) neural network (NN)-based reduced model to accelerate such simulations. The AE NN is first trained to find a low-dimensional latent representation of the ...

The experimental results show that the performance of the LGNN algorithm in some tasks is slightly worse than that of the existing mainstream graph neural network algorithms, but it shows or exceeds ...

It produces mathematical algorithms that are widely used to recognize patterns and solve complex problems in science and business. ANNs, which are also referred to as simulated neural networks ...

💓Let's build the Simplest Possible Autoencoder . ⁉️ 🏷We'll start Simple, with a Single fully-connected Neural Layer as Encoder and as Decoder.