qiskit-machine-learning

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- [ ] Introduce proper time evolution interface in core and required implementations  - [ ] Implement forward & backward pass

adekusar-drl

TODO

dlasecki

Better batch size default setting for QuantumKernel

9

### What is the expected enhancement? The default batch size value of the Quantum Kernel (currently 900) might create unnecessary jobs when the user is not careful. The main reason...

cnktysz

Includes calculating a probability distribution from input data and from a Gibbs state for a Quantum Boltzmann Machine.

dlasecki

The implementation of the Quantum Boltzmann Machine should follow the `NeuralNetwork` interface.

dlasecki

The implementation should make us of gradients calculated from a Gibbs state to calculate gradients of a loss function for a Quantum Boltzmann Machine.

dlasecki

Integrate convolutional neural network quantum circuits with exisiting interfaces.

1

The goal of this issue is to make use of existing interfaces for neural networks and reuse loss functions, optimizers etc. for convolutional quantum neural networks.

dlasecki

Implement quantum circuits for convolutional neural networks.

1

The goal of this issue is to build quantum circuits that execute the quantum part of the processing.

dlasecki

TODO

dlasecki

QBMs consist of visible and hidden units which define a partition of an underlying Gibbs state used for sampling. The goal of this issue is to ignore hidden qubits in...

dlasecki