A Stacked Autoencoder Neural Network Algorithm for Breast Cancer Diagnosis With Magnetic Detection Electrical Impedance Tomography Abstract: Magnetic detection electrical impedance tomography (MDEIT) ...

Here, 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 ...

Autoencoder is a type of neural network where the output layer has the same dimensionality as the input layer. In simpler words, the number of output units in the output layer is equal to the number ...

Incorporating detailed chemical kinetic models is critical for accurate simulations of reacting flows. However, detailed models involve a large number of thermochemical (TC) state variables. Solving ...

Autoencoder neural networks: These unsupervised machine learning systems, sometimes referred to as Autoassociators, ingest unlabeled inputs, encodes data, and then decodes the data as it attempts ...

Training algorithm breaks barriers to deep physical neural networks. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2023 / 12 / 231207161444.htm ...

This is a simple example of using a neural network as an autoencoder without using any machine learning libraries in Python. The input is a 8-bit binary digits and as expected the output is the same 8 ...