Quantum neural networks (qiskit_machine_learning.neural_networks
)¶
A neural network is a parametrized network which may be defined as a artificial neural network  classical neural network  or as parametrized quantum circuits  quantum neural network. Furthermore, neural networks can be defined with respect to a discriminative or generative task.
Neural networks may be used, for example, with the
VQC
algorithm.
See also the TorchConnector
that allows the
use of these neural networks in code written to PyTorch.
Neural Network Base Classes¶
Abstract Neural Network class providing forward and backward pass and handling batched inputs. 

A sampling neural network abstract class for all (quantum) neural networks within Qiskit's machine learning module that generate samples instead of (expected) values. 
Neural Networks¶
Pending deprecation: Opflow Quantum Neural Network. 

Pending deprecation: Two Layer Quantum Neural Network consisting of a feature map, a ansatz, and an observable. 

Pending deprecation: A sampling neural network based on a given quantum circuit. 

A neural network implementation based on the Estimator primitive. 

A neural network implementation based on the Sampler primitive. 
Neural Network Metrics¶
This class computes the global effective dimension for a Qiskit 

This class computes the local effective dimension for a Qiskit 