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Found 7 papers, 1 papers with code
Variational Quantum Circuits Enhanced Generative Adversarial Network
Generative adversarial network (GAN) is one of the widely-adopted machine-learning frameworks for a wide range of applications such as generating high-quality images, video, and audio contents.
Quantum-Inspired Machine Learning for Molecular Docking
Traditional docking by searching for possible binding sites and conformations is computationally complex and results poorly under blind docking.
iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression
We also propose a lossless compression algorithm based on iVPF.
Low-Depth Optical Neural Networks
Optical neural network (ONN) is emerging as an attractive proposal for machine-learning applications, enabling high-speed computation with low-energy consumption.
Quantum Speedup in Adaptive Boosting of Binary Classification
Here we propose a quantum extension of AdaBoost, demonstrating a quantum algorithm that can output the optimal strong classifier with a quadratic speedup in the number of queries of the weak classifiers.
Transforming Bell's Inequalities into State Classifiers with Machine Learning
These results demonstrate how the tools in machine learning can be applied to solving problems in quantum information science.
A variational eigenvalue solver on a quantum processor
Quantum computers promise to efficiently solve important problems that are intractable on a conventional computer.
Quantum Physics Chemical Physics
