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General implementation of quantum physics-informed neural networks

https://doi.org/10.1016/j.array.2023.100287

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9783527805785.ch4openalex-snapshot

Approximate Quantum Cloning

inferredcites →https://doi.org/10.1002/andp.19263851302openalex-snapshot

Quantisierung als Eigenwertproblem

inferredcites →https://doi.org/10.1002/wcms.1481openalex-snapshot

The prospects of quantum computing in computational molecular biology

inferredcites →https://doi.org/10.1007/978-1-4419-9326-7openalex-snapshot

Ensemble Machine Learning: Methods and Applications

inferredcites →https://doi.org/10.1007/978-1-4615-1733-7openalex-snapshot

Data Mining for Scientific and Engineering Applications

inferredcites →https://doi.org/10.1007/978-3-030-99379-5openalex-snapshot

Introduction to Quantum Computing with Q# and QDK

inferredcites →https://doi.org/10.1007/978-3-642-50974-2openalex-snapshot

Information and Classification: Concepts, Methods, and Applications: Proceedings of the 16th Annual Conference of the Gesellschaft Fur Klassifikation E. V. University of Dortmund, April 1-3, 1992

inferredcites →https://doi.org/10.1007/bf01501506openalex-snapshot

The impact of neural networks in finance

inferredcites →https://doi.org/10.1007/s00521-012-1026-yopenalex-snapshot

Fast neural network learning algorithms for medical applications

inferredcites →https://doi.org/10.1007/s00521-020-05340-5openalex-snapshot

The neural network collocation method for solving partial differential equations

inferredcites →https://doi.org/10.1007/s10409-021-01148-1openalex-snapshot

Physics-informed neural networks (PINNs) for fluid mechanics: a review

inferredcites →https://doi.org/10.1016/j.array.2021.100110openalex-snapshot

Physics-informed neural network method for solving one-dimensional advection equation using PyTorch

inferredcites →https://doi.org/10.1016/j.cma.2019.112789openalex-snapshot

Physics-informed neural networks for high-speed flows

inferredcites →https://doi.org/10.1016/j.jcp.2018.10.045openalex-snapshot

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

inferredcites →https://doi.org/10.1016/j.jcp.2020.109672openalex-snapshot

A derivative-free method for solving elliptic partial differential equations with deep neural networks

inferredcites →https://doi.org/10.1016/j.media.2022.102399openalex-snapshot

Physics-informed neural networks for myocardial perfusion MRI quantification

inferredcites →https://doi.org/10.1016/j.neucom.2017.05.025openalex-snapshot

Medical image retrieval using deep convolutional neural network

inferredcites →https://doi.org/10.1016/j.neucom.2021.02.102openalex-snapshot

Quantum Machine Learning: A tutorial

inferredcites →https://doi.org/10.1016/j.rineng.2021.100316openalex-snapshot

A review of physics-based machine learning in civil engineering

inferredcites →https://doi.org/10.1016/s0022-1694(02)00313-xopenalex-snapshot

Geomorphology-based artificial neural networks (GANNs) for estimation of direct runoff over watersheds

inferredcites →https://doi.org/10.1016/s0304-3800(01)00316-7openalex-snapshot

Applications of machine learning to ecological modelling

inferredcites →https://doi.org/10.1017/s0956792520000182openalex-snapshot

Solving parametric PDE problems with artificial neural networks

inferredcites →https://doi.org/10.1021/acs.jpclett.9b03664openalex-snapshot

Quantum Chemistry in the Age of Machine Learning

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1038/543171aopenalex-snapshot

Commercialize quantum technologies in five years

inferredcites →https://doi.org/10.1038/nature23474openalex-snapshot

Quantum machine learning

inferredcites →https://doi.org/10.1038/nrg3920openalex-snapshot

Machine learning applications in genetics and genomics

inferredcites →https://doi.org/10.1038/s41467-019-12875-2openalex-snapshot

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

inferredcites →https://doi.org/10.1038/s41467-022-32550-3openalex-snapshot

Generalization in quantum machine learning from few training data

inferredcites →https://doi.org/10.1038/s41573-019-0024-5openalex-snapshot

Applications of machine learning in drug discovery and development

inferredcites →https://doi.org/10.1038/s42256-018-0006-zopenalex-snapshot

Designing neural networks through neuroevolution

inferredcites →https://doi.org/10.1038/s43588-022-00311-3openalex-snapshot

Challenges and opportunities in quantum machine learning

inferredcites →https://doi.org/10.1038/srep00260openalex-snapshot

An Efficient Exact Quantum Algorithm for the Integer Square-free Decomposition Problem

inferredcites →https://doi.org/10.1080/00107514.2014.964942openalex-snapshot

An introduction to quantum machine learning

inferredcites →https://doi.org/10.1080/09500349708231894openalex-snapshot

Prescription for experimental determination of the dynamics of a quantum black box

inferredcites →https://doi.org/10.1088/0034-4885/61/2/002openalex-snapshot

Quantum computing

inferredcites →https://doi.org/10.1103/physreva.103.052416openalex-snapshot

Solving nonlinear differential equations with differentiable quantum circuits

inferredcites →https://doi.org/10.1103/physreva.65.042105openalex-snapshot

Diluting quantum information: An analysis of information transfer in system-reservoir interactions

inferredcites →https://doi.org/10.1103/physrevlett.122.250501openalex-snapshot

Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems

inferredcites →https://doi.org/10.1109/2.32openalex-snapshot

A neural network for visual pattern recognition

inferredcites →https://doi.org/10.1109/2.33openalex-snapshot

The ART of adaptive pattern recognition by a self-organizing neural network

inferredcites →https://doi.org/10.1109/69.553163openalex-snapshot

Effective data mining using neural networks

inferredcites →https://doi.org/10.1109/72.712178openalex-snapshot

Artificial neural networks for solving ordinary and partial differential equations

inferredcites →https://doi.org/10.1109/icieam.2016.7911596openalex-snapshot

Neural networks in data mining

inferredcites →https://doi.org/10.1109/icppw.2003openalex-snapshot

2003 International Conference on Parallel Processing Workshops, 2003. Proceedings.

inferredcites →https://doi.org/10.1109/icsmc.1999.814023openalex-snapshot

IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028)

inferredcites →https://doi.org/10.1109/msp.2017.2760358openalex-snapshot

Using Deep Neural Networks for Inverse Problems in Imaging: Beyond Analytical Methods

inferredcites →https://doi.org/10.1109/tbdata.2017.2717439openalex-snapshot

Deep Feature Learning for Medical Image Analysis with Convolutional Autoencoder Neural Network

inferredcites →https://doi.org/10.1109/tnnls.2015.2416771openalex-snapshot

A Spiking Neural Network System for Robust Sequence Recognition

inferredcites →https://doi.org/10.1142/s021962200700237xopenalex-snapshot

NEURAL NETWORKS IN FINANCE AND ECONOMICS FORECASTING

inferredcites →https://doi.org/10.1146/annurev-conmatphys-031119-050605openalex-snapshot

Superconducting Qubits: Current State of Play

inferredcites →https://doi.org/10.1155/2021/4040497openalex-snapshot

A Partial Differential Equation-Based Image Restoration Method in Environmental Art Design

inferredcites →https://doi.org/10.1155/2021/5569645openalex-snapshot

Physics Informed by Deep Learning: Numerical Solutions of Modified Korteweg-de Vries Equation

inferredcites →https://doi.org/10.2172/2377336openalex-snapshot

Out-of-distribution generalization for learning quantum dynamics

inferredcites →https://doi.org/10.2478/v10136-012-0031-xopenalex-snapshot

Artificial neural networks in medical diagnosis

inferredcites →https://doi.org/10.3389/fphy.2020.00042openalex-snapshot

Physics-Informed Neural Networks for Cardiac Activation Mapping

inferredcites →https://doi.org/10.48550/arxiv.1810.13306openalex-snapshot

Automated Machine Learning: From Principles to Practices

inferredcites →https://doi.org/10.48550/arxiv.1912.00873openalex-snapshot

Variational Physics-Informed Neural Networks For Solving Partial Differential Equations

inferredcites →https://doi.org/10.48550/arxiv.2211.04607openalex-snapshot

First principles physics-informed neural network for quantum wavefunctions and eigenvalue surfaces

inferredcites →https://doi.org/10.82308/49932openalex-snapshot

Artificial neural networks and their application to sequence recognition

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A Comprehensive Survey on Quantum Learning and Quantum Machine Learning

inferred← citeshttps://doi.org/10.1016/j.asoc.2026.115956openalex-snapshot

Recent advancements in quantum machine learning applications: A review from smart grid viewpoint

inferred← citeshttps://doi.org/10.1016/j.nexres.2026.101897openalex-snapshot

Quantum-enabled construction (QEC): A framework of quantum technology in construction and built environments

inferred← citeshttps://doi.org/10.1016/j.oceaneng.2025.123482openalex-snapshot

Quantum machine learning for wave overtopping estimation: Integrating with causal inference and uncertainty quantification

inferred← citeshttps://doi.org/10.1080/00207160.2026.2713517openalex-snapshot

An enhanced physics-informed deep learning framework for solving variable-coefficient heat conduction problems with temperature-dependent thermal conductivity and nonlinear source terms

inferred← citeshttps://doi.org/10.1103/fdd3-qz1sopenalex-snapshot

Classical-quantum hybrid architecture for physics-informed neural networks

inferred← citeshttps://doi.org/10.1109/access.2025.3599147openalex-snapshot

A Review on Quantum Machine Learning in Applied Systems and Engineering

inferred← citeshttps://doi.org/10.1109/icses63760.2024.10910583openalex-snapshot

Quantum-Enhanced Spiking Neural Networks for Closed-Loop Neuromodulation Systems: A Theoretically Advanced Framework

inferred← citeshttps://doi.org/10.1140/epjc/s10052-025-14942-zopenalex-snapshot

Towards asteroseismology of neutron stars with physics-informed neural networks

inferred← citeshttps://doi.org/10.1515/9783111619323-003openalex-snapshot

393 Securing the Skies: Safety Queuing Models for Quantum Drone Ad Hoc Networks

inferred← citeshttps://doi.org/10.3390/ai5010015openalex-snapshot

Forging the Future: Strategic Approaches to Quantum AI Integration for Industry Transformation

inferred← citeshttps://doi.org/10.3390/quantum6040039openalex-snapshot

Quantum Computing: Navigating the Future of Computation, Challenges, and Technological Breakthroughs

inferred← citeshttps://doi.org/10.36227/techrxiv.24478663openalex-snapshot

Quantum Computing for Climate Change Detection, Climate Modeling, and Climate Digital Twin

inferred← citeshttps://doi.org/10.36227/techrxiv.24478663.v1openalex-snapshot

Quantum Computing for Climate Change Detection, Climate Modeling, and Climate Digital Twin

inferred← citeshttps://doi.org/10.4018/979-8-3693-6225-9.ch010openalex-snapshot

Role of Infinity in Shaping Financial Reality From a Quantum Finance Perspective

inferred← citeshttps://doi.org/10.53355/zhu.2025.117.4.002openalex-snapshot

RESEARCH AND ANALYSIS OF THE NEURAL NETWORK IMPLEMENTATION IN TEACHING PHYSICS IN HIGHER EDUCATION

inferred← citeshttps://doi.org/10.70675/9b5a5d8dzb45fz40c8z9799zf8200a2ac483openalex-snapshot

Physics-based deep representation learning of vegetation using optical satellite image time series

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