Cover Image

QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Farea, Afrah, Khan, Saiful, Celebi, Mustafa Serdar
Format:	Preprint
Published:	2025
Subjects:	Quantum Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learnable Activation Functions in Physics-Informed Neural Networks for Solving Partial Differential Equations
by: Farea, Afrah, et al.
Published: (2024)

Multi-Objective Loss Balancing in Physics-Informed Neural Networks for Fluid Flow Applications
by: Farea, Afrah, et al.
Published: (2025)

Learning Fluid-Structure Interaction with Physics-Informed Machine Learning and Immersed Boundary Methods
by: Farea, Afrah, et al.
Published: (2025)

Physics-Informed Neural Networks for Solving Derivative-Constrained PDEs
by: Hoshisashi, Kentaro, et al.
Published: (2026)

Quantum Noise Tomography with Physics-Informed Neural Networks
by: Sulc, Antonin
Published: (2025)

Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quantum Convolutional Neural Networks
by: Zhai, Jucai, et al.
Published: (2026)

Quantum Convolutional Neural Networks are Effectively Classically Simulable
by: Bermejo, Pablo, et al.
Published: (2024)

Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
by: Wang, Huaxin, et al.
Published: (2026)

Building Continuous Quantum-Classical Bayesian Neural Networks for a Classical Clinical Dataset
by: Sakhnenko, Alona, et al.
Published: (2024)

Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations
by: Rao, Xiang, et al.
Published: (2025)

Quantum Convolutional Neural Networks with Interaction Layers for Classification of Classical Data
by: Mahmud, Jishnu, et al.
Published: (2023)

Self-Adaptive Physics-Informed Quantum Machine Learning for Solving Differential Equations
by: Setty, Abhishek, et al.
Published: (2023)

Hybrid Quantum-Classical Neural Networks for Few-Shot Credit Risk Assessment
by: Wang, Zheng-an, et al.
Published: (2025)

Hybrid Quantum-Classical Neural Architecture Search
by: Marchisio, Alberto, et al.
Published: (2026)

Variational Quantum Physics-Informed Neural Networks for Hydrological PDE-Constrained Learning with Inherent Uncertainty Quantification
by: Hewage, Prasad Nimantha Madusanka Ukwatta, et al.
Published: (2026)

AQ-PINNs: Attention-Enhanced Quantum Physics-Informed Neural Networks for Carbon-Efficient Climate Modeling
by: Dutta, Siddhant, et al.
Published: (2024)

Towards Arbitrary QUBO Optimization: Analysis of Classical and Quantum-Activated Feedforward Neural Networks
by: Lai, Chia-Tso, et al.
Published: (2024)

Winning Lottery Tickets in Neural Networks via a Quantum-Inspired Classical Algorithm
by: Isogai, Natsuto, et al.
Published: (2026)

Deep Neural Network Emulation of the Quantum-Classical Transition via Learned Wigner Function Dynamics
by: Majid, Kamran
Published: (2025)

How Embeddings Shape Graph Neural Networks: Classical vs Quantum-Oriented Node Representations
by: Innan, Nouhaila, et al.
Published: (2026)

Exponential Quantum Speedup for Simulation-Based Optimization Applications
by: Stein, Jonas, et al.
Published: (2023)

The Role of Quantum in Hybrid Quantum-Classical Neural Networks: A Realistic Assessment
by: Freinberger, Dominik, et al.
Published: (2026)

IQNN-CS: Interpretable Quantum Neural Network for Credit Scoring
by: Khan, Abdul Samad, et al.
Published: (2025)

Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation
by: Hasan, Mohammad Junayed, et al.
Published: (2023)

Hybrid Quantum-Classical Recurrent Neural Networks
by: Xu, Wenduan
Published: (2025)

Quantum-Classical Machine learning by Hybrid Tensor Networks
by: Liu, Ding, et al.
Published: (2020)

On Emergences of Non-Classical Statistical Characteristics in Classical Neural Networks
by: Zhao, Hanyu, et al.
Published: (2026)

Quantum Neural Networks in Practice: A Comparative Study with Classical Models from Standard Data Sets to Industrial Images
by: Basilewitsch, Daniel, et al.
Published: (2024)

A Comparison Between Invariant and Equivariant Classical and Quantum Graph Neural Networks
by: Forestano, Roy T., et al.
Published: (2023)

Quantitative Evaluation of Quantum/Classical Neural Network Using a Game Solver Metric
by: Kamei, Suzukaze, et al.
Published: (2025)

Quantum-Enhanced Generative Adversarial Networks: Comparative Analysis of Classical and Hybrid Quantum-Classical Generative Adversarial Networks
by: Goh, Kun Ming
Published: (2025)

FRQI Pairs method for image classification using Quantum Recurrent Neural Network
by: Potempa, Rafał, et al.
Published: (2025)

QINNs: Quantum-Informed Neural Networks
by: Bal, Aritra, et al.
Published: (2025)

Quantum-Classical Hybrid Molecular Autoencoder for Advancing Classical Decoding
by: Jahin, Afrar, et al.
Published: (2025)

$\mathbb{Z}_2\times \mathbb{Z}_2$ Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
by: Dong, Zhongtian, et al.
Published: (2023)

On the Interpretability of Quantum Neural Networks
by: Pira, Lirandë, et al.
Published: (2023)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits
by: Nicoli, Kim A., et al.
Published: (2024)

Quantum HyperNetworks: Training Binary Neural Networks in Quantum Superposition
by: Carrasquilla, Juan, et al.
Published: (2023)

Q-Newton: Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent
by: Li, Pingzhi, et al.
Published: (2024)

A Hybrid Quantum-Classical Physics-Informed Neural Network Architecture for Solving Quantum Optimal Control Problems
by: Dehaghani, Nahid Binandeh, et al.
Published: (2024)