A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Using an algorithm they call the Krakencoder, researchers at Weill Cornell Medicine are a step closer to unraveling how the ...

Kaizen rethinks cell segmentation by mimicking brain predictions. Using an iterative machine-learning approach to refine boundaries in crowded microscopy images, it enhances accuracy in tissue studies ...

An autoencoder is an unsupervised learning model designed to encode input data ... exclusive holographic LiDAR point cloud algorithms architecture design, breakthrough technical holographic ...

Reservoir rock porosity is usually determined by core analysis, but the cost of this method is huge, in order to establish a more accurate and stable reservoir porosity prediction model. Using the ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...

Motivated by these benefits, this research aims to design a lightweight autoencoder deep model that has a shallow architecture ... several optimizers such as Arithmetic Optimization Algorithm (AOA), ...

The demo sets up training parameters for the batch size (10), number of epochs to train (100), loss function (mean squared error), optimization algorithm (stochastic ... create autoencoder net # 3.

Abstract: Magnetic compensation is a necessary step in the aeromagnetic data processing. While the aeromagnetic compensation model is a linear regression model, the multicollinearity of the variables ...