Researchers have discovered two vulnerabilities in the widely used Cursor AI-enabled integrated development environment (IDE) ...

Abstract: In-memory computing (IMC) is an effective solution for energy-efficient artificial intelligence applications. Analog IMC amortizes the power consumption of multiple sensing amplifiers with ...

Derived types that mimic vector and tensor fields and Differential and integral operators for writing vector and tensor expressions. Formal's types and operators implement the discrete calculus of ...

This repository contains an implementation of symmetry-adapted Gaussian Process Regression suitable to perform equivariant learning and prediction of the electron density of molecular and ...

In recent years, neural networks have once again triggered an increased interest among researchers in the machine learning community. So-called deep neural networks model functions using a composition ...

We present two fiberized vector magnetic-field sensors, based on nitrogen-vacancy (NV) centers in diamond. The sensors feature sub-nT/ magnetic sensitivity. We use commercially available components to ...

Detecting genetic variants associated with the variance of complex traits can provide crucial insights into the interplay between genes and environments and how they jointly shape human phenotypes in ...

U of T computer vision expert to lead new Nvidia research lab in Toronto Sanja Fidler, an expert in computer vision and applied machine learning, is the latest U of T researcher to be tapped to run a ...