The algorithm consists of two networks, an Actor and a Critic network, which approximate the policy and value functions of a reinforcement learning problem. The name ...

Artificial Intelligence systems powered by deep learning are changing how we work, communicate, and make decisions. If we want these technologies to serve society responsibly, tomorrow’s citizens need ...

This important study introduces a fully differentiable variant of the Gillespie algorithm as an approximate stochastic simulation scheme for complex chemical reaction networks, allowing kinetic ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. A critical bottleneck for the training of large neural networks (NNs) is communication ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

Abstract: NARA-WPE is a Python software package providing implementations of the weighted prediction error (WPE) dereverberation algorithm. WPE has been shown to be a ...

Emerging two-terminal nanoscale memory devices, known as memristors, have demonstrated great potential for implementing energy-efficient neuro-inspired computing architectures over the past decade. As ...