The following are 2nd modifications or improvements to original notebooks prior to August 25, 2023 for 1) Faster runtimes, 2) Lower losses, or 3) Higher accuracies. The goal of Qiskit tutorials is to provide fundamental quantum computational building blocks, and allow for rapid prototyping without deep quantum computing knowledge. The objective of PennyLane demos is to offer a Quantum Differentiable programming open source software library for training the entire structure of the Quantum Model. Both libraries provide a framework for creating new R&D applications in fields such as Medical.

38 Qiskit, PennyLane QML/QiML Demos November 2023 Seminar, 1st modifications Qiskit October 2023 Seminar, 1st modifications PennyLane August 2023 Seminar.

Please refer to the authors' models for the published primary work.

QK01 Quantum Neural Networks Original Model

QK02 Classifier & Regressor Original Model,

QK03 Training on a Real Dataset Original Model,

QK04 Quantum Kernel ML Original Model,

QK05 PyTorch qGAN Original Model,

QK06 Torch Connector Original Model,

QK07 Pegasos QSVM Original Model,

QK08 Quantum Kernel Training Original Model,

QK09 Qiskit ML Model Original Model,

QK10 Effective Dimension Original Model,

QK11 Quantum CNN Original Model,

QK12 Quantum Autoencoder Original Model.

PL13 Equivariant Graph Original PennyLane Model,

PL14 Time Series Original PennyLane Model,

PL15 Geometric QML Original PennyLane Model,

PL16 Generalization in QML Original PennyLane Model,

PL17 Function Fitting Original PennyLane Model,

PL18 Many Body Original PennyLane Model,

PL19 Learn from Experiments, Classification Original PennyLane Model,

PL20 Tensor Network Original PennyLane Model,

PL21 Approximate Kernel Original PennyLane Model,

PL22 Quantum GANs Original PennyLane Model,

PL23 Unitary Designs Original PennyLane Model,

PL24 Quantum Kernels, Classification Original PennyLane Model,

PL25 Haar Measure Original PennyLane Model,

PL26 Learn QNNs, Speed Original PennyLane Model,

PL27 Kernel Scikit-Learn Original PennyLane Model,

PL28 Keras Layers Original PennyLane Model,

PL29 Torch Layers Original PennyLane Model,

PL30 Fourier Series Original PennyLane Model,

PL31 Quantum Graph RNN Original PennyLane Model,

PL32 Quanvolutional NN Original PennyLane Model,

PL33 Ensemble Classification Original PennyLane Model,

PL34 Quantum Transfer Learning Original PennyLane Model,

PL35 Photonic Quantum NN Original PennyLane Model,

PL36 GANs Cirq TensorFlow Original PennyLane Model,

PL37 Data-Reuploading Original PennyLane Model,

PL38 Variational Classifier Original PennyLane Model.