Quantum-ML.
Developed
Cutting-edge framework integrating quantum computing with machine learning. Enables high-performance quantum tasks directly through an API.
Core Architecture
Quantum Kernels
Utilization of high-dimensional Hilbert spaces for feature mapping and enhanced classification boundaries.
PyTorch Bridge
Seamless integration with PyTorch tensors, allowing quantum circuits to function as trainable neural network layers.
Variational Circuits
Optimized parameterized quantum circuits (PQCs) for generative modeling and reinforcement learning tasks.
Data Encoding
Efficient schemes for encoding classical data into quantum states, maximizing bandwidth and minimizing qubit usage.