Quantum Neural Network

Quantum neural networks (QNNs) leverage quantum computing principles to enhance machine learning capabilities, primarily aiming to improve the speed, accuracy, and efficiency of various learning tasks. Current research focuses on developing novel QNN architectures, such as continuous-time recurrent and liquid QNNs, and exploring efficient training algorithms to overcome challenges like barren plateaus, often employing techniques like swarm optimization or knowledge distillation from classical networks. This field is significant because QNNs offer the potential for quantum advantage in diverse applications, including image classification, power system simulations, and genomic data analysis, although the extent of this advantage and the practical scalability remain active areas of investigation.

Papers

November 23, 2023

Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation
Mohammad Junayed Hasan, M. R. C. Mahdy
Knowledge Distillation Quantum Machine Learning Knowledge Transfer Quantum Computing Quantum Physic Quantum Neural Network Bridging Text Quantum Classical Quantum Model

November 4, 2023

Quantum Neural Networks for Power Flow Analysis
Zeynab Kaseb, Matthias Moller, Giorgio Tosti Balducci, Peter Palensky, Pedro P. Vergara
Quantum Neural Network Classical Neural Network Power Flow Quantum Classical Neural Network

October 3, 2023

Approximately Equivariant Quantum Neural Network for $p4m$ Group Symmetries in Images
Su Yeon Chang, Michele Grossi, Bertrand Le Saux, Sofia Vallecorsa
Quantum Algorithm Quantum Neural Network Variational Quantum Algorithm Equivariant Quantum Neural Network

September 26, 2023

Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks
Hao-kai Zhang, Chenghong Zhu, Mingrui Jing, Xin Wang
Quantum Machine Learning Quantum Neural Network Quantum State Quantum Advantage Statistical Analysis Unknown Quantum

September 6, 2023

Let Quantum Neural Networks Choose Their Own Frequencies
Ben Jaderberg, Antonio A. Gentile, Youssef Achari Berrada, Elvira Shishenina, Vincent E. Elfving
Quantum Neural Network Parameterized Quantum Circuit Quantum Model Variational Quantum Machine Learning

August 22, 2023

On the Interpretability of Quantum Neural Networks
Lirandë Pira, Chris Ferrie
Inherent Interpretability Quantum Physic Quantum Neural Network Model Agnostic Quantum State Quantum AI

August 18, 2023

Variational optimization of the amplitude of neural-network quantum many-body ground states
Jia-Qi Wang, Rong-Qiang He, Zhong-Yi Lu
Quantum Neural Network Many Body Variational Quantum Renormalization Group Amplitude Estimation Neural Network Quantum State Variational Optimization

July 28, 2023

A supervised hybrid quantum machine learning solution to the emergency escape routing problem
Nathan Haboury, Mo Kordzanganeh, Sebastian Schmitt, Ayush Joshi, Igor Tokarev, Lukas Abdallah, Andrii Kurkin, Basil Kyriacou, Alexey Melnikov
Quantum Machine Learning Solution Path Quantum Physic Quantum Neural Network Hybrid Quantum Classical Hurricane Evacuation Escape Route

July 24, 2023

Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs
Lukas Gonon, Antoine Jacquier
Neural Network Quantum Physic Quantum Circuit Quantum Neural Network Universal Approximation Function Approximation Error Bound Classical Neural Network Quantum Reservoir

July 23, 2023

DyPP: Dynamic Parameter Prediction to Accelerate Convergence of Variational Quantum Algorithms
Satwik Kundu, Debarshi Kundu, Swaroop Ghosh
Early Stage Convergence Quantum Neural Network Variational Quantum Algorithm Variational Quantum Quantum Approximate Optimization Algorithm Quantum Simulator

July 16, 2023

Computing the gradients with respect to all parameters of a quantum neural network using a single circuit
Guang Ping He
Natural Gradient Quantum Circuit Many Parameter Quantum Neural Network Digital Computing Depth Circuit Parameter Shift

May 31, 2023

Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning Algorithms
Mst Shapna Akter, Md Jobair Hossain Faruk, Nafisa Anjum, Mohammad Masum, Hossain Shahriar, Akond Rahman, Fan Wu, Alfredo Cuzzocrea
Quantum Machine Learning Source Code Quantum Neural Network Supply Chain Performance Comparison

May 22, 2023

On quantum backpropagation, information reuse, and cheating measurement collapse
Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean
Quantum Machine Learning Quantum Neural Network Quantum Information Data Recycling Parameterized Quantum Quantum Resource

May 17, 2023

Deep quantum neural networks form Gaussian processes
Diego García-Martín, Martin Larocca, M. Cerezo
Neural Network Gaussian Process Quantum Neural Network Hilbert Space Deep Quantum Shallow Quantum Circuit

May 15, 2023

April 25, 2023

The cross-sectional stock return predictions via quantum neural network and tensor network
Nozomu Kobayashi, Yoshiyuki Suimon, Koichi Miyamoto, Kosuke Mitarai
Neural Network Human Prediction Quantum Physic Quantum Neural Network Stock Market Stock Return Prediction Quantum Inspired Machine Learning Model Benchmark Scalable Quantum

April 24, 2023

Quantum Machine Learning Approach for the Prediction of Surface Roughness in Additive Manufactured Specimens
Akshansh Mishra, Vijaykumar S. Jatti
Human Prediction Quantum Machine Learning Quantum Neural Network Variational Quantum Classifier Deep Forest Surface Roughness

April 15, 2023

Learning To Optimize Quantum Neural Network Without Gradients
Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Ilya Safro
LeArning Abstract Quantum Machine Learning Quantum Circuit Quantum Neural Network Quantum Hardware Quantum Classical

March 26, 2023

Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels
Xuchen You, Shouvanik Chakrabarti, Boyang Chen, Xiaodi Wu
Neural Network Early Stage Convergence Neural Tangent Kernel Quantum Neural Network Intermediate Scale Quantum Subject Level Deviation Quantum Version

Quantum Neural Network

Papers

Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation

Quantum Neural Networks for Power Flow Analysis

Approximately Equivariant Quantum Neural Network for $p4m$ Group Symmetries in Images

Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks

Let Quantum Neural Networks Choose Their Own Frequencies

On the Interpretability of Quantum Neural Networks

Variational optimization of the amplitude of neural-network quantum many-body ground states

A supervised hybrid quantum machine learning solution to the emergency escape routing problem

Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs

DyPP: Dynamic Parameter Prediction to Accelerate Convergence of Variational Quantum Algorithms

Computing the gradients with respect to all parameters of a quantum neural network using a single circuit

Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning Algorithms

On quantum backpropagation, information reuse, and cheating measurement collapse

Deep quantum neural networks form Gaussian processes

Quantum Neural Network for Quantum Neural Computing

Biomarker Discovery with Quantum Neural Networks: A Case-study in CTLA4-Activation Pathways

The cross-sectional stock return predictions via quantum neural network and tensor network

Quantum Machine Learning Approach for the Prediction of Surface Roughness in Additive Manufactured Specimens

Learning To Optimize Quantum Neural Network Without Gradients

Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels