A quantum-enhanced generative adversarial network for high-dimensional data synthesis.
Leverage quantum computing principles to accelerate model training for complex data distributions.
Generate and manipulate high-dimensional data such as images, audio, and structured datasets.
Built with flexibility in mind—extend and customize the quantum integration layers as needed.
Distribute computations across GPUs and quantum processors with built-in parallelism.
Seamlessly integrates quantum and classical layers for optimal performance.
Pre-trained models for common domains like images, speech, and text generation.
Install quantumgan via pip and choose a training mode.
pip install quantumgan
quantumgan.train.classical()
for classical backends.
quantumgan.train.quantum()
for quantum processors (requires Qiskit or Cirq).