According to Hlavac, the types of neural networks that will be most frequently used by companies in the future have to not only solve a business problem but also achieve high accuracy and provide ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

LSTM Recurrent Neural Network is a special version of the RNN model. It stands for Long Short-Term Memory. The simple RNN has a problem that it cannot remember the context in a long sentence because ...

Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

A research paper titled “ Liquid Time-constant Networks,” published at the tail end of 2020 by Hasani, Rus, Lechner, Amini and others, put liquid neural networks on the map following several ...

The premier tools at the time for image-related tasks like this were convolutional neural networks (CNNs). For the Chinese handwriting task, a writer would trace a character on a digital tablet ...

OneFlip is a Rowhammer-based attack that flips a single bit in neural network weights to stealthily backdoor AI systems.