QC Ware just finished a 6-month long collaboration with Roche, focused on Medical Image Classification using Quantum Neural Networks (QNNs).

In this Tech Talk, Natansh will describe the new types of QNNs developed by the QML sub-team of the Paris Team. There shall be a brief discussion on primarily two types of Neural Networks, namely, Orthogonal Neural Networks (OrthoNNs) and Quantum-Assisted Neural Networks (qaNNs). OrthoNNs (https://arxiv.org/abs/2106.07198) are a class of fully connected neural networks with orthogonal weight matrices, making them suitable for quantum computers. qaNNs are classical neural networks that are assisted by a quantum processing unit to calculate dot products. In this talk, we shall embark on a journey through the theory (with a brief look at the algorithms), the application on medical image classification and a discussion over their further potential use-cases. We shall try to be technical enough to continue detailed discussions later but not get bored.

In this talk, Alicia will explain what QC Ware is doing to prepare for and lead the quantum revolution in chemistry