IEEE

Adaptive Output Feedback Control Using Lyapunov-Based Deep Recurrent Neural Networks (Lb-DRNNs)

Abstract: Unlike traditional feedforward neural networks, recurrent neural networks (RNNs) possess a recurrent connection that allows them to retain past information. This internal memory enables RNNs ...
VentureBeat

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...
GitHub

This repo describes python code and input data files for "Forecasting stock return distributions around the globe with quantile neural networks".

Inputs: describes all the raw inputs to run the code Code description: describes the python code and how to run it Code to figure mapping: provides mapping of figures in the paper to code used to ...
IEEE

Non-Negative Gated Recurrent Neural Networks

Abstract: Neural networks have become increasingly popular in recent years due to their ability to efficiently solve a wide range of complex problems, including computer vision, machine translation, ...