The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Abstract: Quantum Machine Learning (QML) has emerged as a promising frontier within artificial intelligence, offering enhanced data-driven modeling through quantum-augmented representation, ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...

Abstract: Quantum Federated Learning (QFL) recently becomes a promising approach with the potential to revolutionize Machine Learning (ML). It merges the established strengths of classical Federated ...