Neural

A deep dive into the world of computational modeling and its applicationsFor a long time, scientists have sought to grasp how humans make decisions — whether we’re selecting what to eat for lunch or...

When there are more features than model dimensionsIt could be ideal if the world of neural network represented a one-to-one relationship: each neuron prompts on one and just one feature. In such a world,...

Once the network has been trained, though, things get way, way cheaper. Petersen compared his logic-gate networks with a cohort of other ultra-efficient networks, akin to binary neural networks, which use simplified perceptrons that...

The e-commerce industry has seen remarkable progress over the past decade, with 3D rendering technologies revolutionizing how customers interact with products online. Static 2D images are not any longer enough to capture the eye...

A simple step-by-step guide to getting began with Neural Networks for Time Series ForecastingForecasting multiple time series can quickly develop into an advanced task; traditional approaches either require a separate model per series (i.e....

A brand new research paper from Canada has proposed a framework that deliberately introduces JPEG compression into the training scheme of a neural network, and manages to acquire higher results – and higher resistance...

At the start, we'd like synthetic data to work with. The info should exhibit some non-linear dependency. Let’s define it like this:I’d like to see you surfaces, so please be at liberty to share...

Neural networks have been on the forefront of AI advancements, enabling the whole lot from natural language processing and computer vision to strategic gameplay, healthcare, coding, art and even self-driving cars. Nevertheless, as these...