AI requires a lot of data, particularly for training models. The problem is that planar chips are unable to process all that ...

In this work, we specifically focus on employing a three-layer tanh neural network within the framework of the deep Ritz method (DRM) to solve second-order elliptic equations with three different ...

The past two years have turned “modernization” from an IT objective into a board-level survival metric. Whether the driver is data-privacy regulation, escalating cloud costs, or the carbon intensity ...

The latest version of Granulator – more of a new instrument than a straight update – both refines and simplifies the granular ...

Use precise geolocation data and actively scan device characteristics for identification. This is done to store and access ...

BNPool is a layer for GNN architectures for graph classification and node clustering. BNPool leverages a Bayesian non-parametric approach to dynamically group nodes based on their features, the graph ...

One of the most popular recent areas of machine learning predicates the use of neural networks (NNs) augmented by information about the underlying process in the form of partial differential equations ...

Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

Using the analogy of the interconnected neural pathways in the brain, network leadership is about harnessing connections to ...

The third article in the Bitcoin Layer 2 series. This article covers the Lightning Network created by Joseph Poon and Tadge ...