Geometric QML

Geometric Quantum Machine Learning (GQML) leverages the principles of quantum mechanics and geometric algebra to design efficient quantum algorithms for machine learning tasks. Current research focuses on developing GQML protocols for specific problems, such as function classification and flood prediction, often integrating classical machine learning techniques for improved performance and scalability. This approach holds promise for accelerating drug discovery and enhancing autonomous driving systems, demonstrating the potential of GQML to address complex real-world challenges.