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Quantum Shadow Gradient Descent for Variational Quantum Algorithms
The dataset used in this paper is a set of quantum states for training a variational quantum algorithm. -
Autonomous Vehicle Dataset
The dataset used in the paper is a collection of autonomous vehicle scenarios, where each scenario is represented as a 3x3 grid encoding. The scenarios are encoded using Pauli-X... -
Tic-Tac-Toe Dataset
The dataset used in the paper is a collection of tic-tac-toe games, where each game is represented as a 9-qubit encoding. The games are encoded using Pauli-X rotations on... -
Policy Gradients using Variational Quantum Circuits
Variational Quantum Circuits are being used as versatile Quantum Machine Learning models. Some empirical results exhibit an advantage in supervised and generative learning... -
Performance of the measurement-based adaptation protocol for the cat state case
A dataset of 2000 initial random states for the cat state case, with mean fidelity for 2000 initial random states, and evolution of ∆ in each iteration. -
Performance of the measurement-based adaptation protocol for the coherent sta...
A dataset of 2000 initial random states for the coherent state case, with mean fidelity for 2000 initial random states, and evolution of ∆ in each iteration. -
Performance of the measurement-based adaptation protocol for the d-dimensiona...
A dataset of 2000 initial random states for the d-dimensional qudit case, with mean fidelity for 2000 initial random states, and evolution of ∆ in each iteration. -
Performance of the measurement-based adaptation protocol for the qubit case
A dataset of 2000 initial random states for the qubit case, with mean fidelity for 2000 initial random states, and evolution of ∆ in each iteration. -
Measurement-based adaptation protocol with quantum reinforcement learning
A quantum reinforcement learning protocol to adapt a quantum state (the agent) to another, unknown, quantum state (the environment). -
Classification of the Fashion-MNIST Dataset on a Quantum Computer
The Fashion-MNIST dataset is a multiclass classification dataset. It contains 70,000 28x28 grayscale images, with 10 classes. -
Temporal Data Processing
The dataset used in the paper is a temporal data processing dataset, which is processed by quantum-classical adaptive gating mechanisms. -
Quantum neural network autoencoder and classifier applied to an industrial cas...
Quantum neural network autoencoder and classifier applied to an industrial case study -
Resource-Efficient Quantum Generative Diffusion Model
The Resource-Efficient Quantum Generative Diffusion Model (RE-QGDM) is a variant of the Quantum Generative Diffusion Model (QGDM) that minimizes the need for auxiliary qubits... -
Quantum Generative Diffusion Model
The Quantum Generative Diffusion Model (QGDM) is a fully quantum-mechanical model for generating quantum state ensembles, inspired by Denois-ing Diffusion Probabilistic Models. -
Hybrid Quantum-Classical Neural Network with Deep Residual Learning
A hybrid quantum-classical neural network with deep residual learning to improve the performance of cost function for deeper networks.
