WiMi also plans to combine the attentional autoencoder network with other advanced recommendation technologies to further enhance recommendation effectiveness.

Compared to using PCA for dimensionality reduction, using a neural autoencoder has the big advantage that it works with source data that contains both numeric and categorical data, while PCA works ...

The Data Science Lab Data Anomaly Detection Using a Neural Autoencoder with C# 04/15/2024 Get Code Download Data anomaly detection is the process of examining a set of source data to find data items ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI.

Inspired by microscopic worms, Liquid AI’s founders developed a more adaptive, less energy-hungry kind of neural network. Now the MIT spin-off is revealing several new ultraefficient models.

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

OpenAI peeks into the “black box” of neural networks with new research "We do not understand" how LLMs work, admits OpenAI in quest to make them interpretable.

Liquid AI, a new MIT spinoff, has raised nearly $40 million in a seed round to build an entirely new type of AI called a liquid neural network.

The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural ...