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Quantum Machine Learning (QML) primitives and layers
This module provides building blocks for quantum machine learning, including parameterized quantum circuits, data encoding strategies, and common QML layer patterns.
Re-exports§
pub use layers::Parameter;
Modules§
- encoding
- Data encoding strategies for quantum machine learning
- generative_
adversarial - Quantum Generative Adversarial Networks (QGANs)
- layers
- Common quantum machine learning layers
- nlp
- Quantum Machine Learning for Natural Language Processing
- reinforcement_
learning - Quantum Reinforcement Learning Algorithms
- training
- Training utilities for quantum machine learning
Structs§
- QMLCircuit
- A parameterized quantum circuit for QML
- QMLConfig
- Configuration for QML circuits
Enums§
- Encoding
Strategy - Data encoding strategies for QML
- Entanglement
Pattern - Entanglement patterns for QML layers
Traits§
- QMLLayer
- Trait for quantum machine learning layers
Functions§
- create_
entangling_ gates - Helper function to create entangling gates based on pattern
- natural_
gradient - Natural gradient for quantum optimization
- quantum_
fisher_ information - Compute the quantum Fisher information matrix