Image de couverture de livre

Learning PDEs for Portfolio Optimization with Quantum Physics-Informed Neural Networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Letao, Lisser, Abdel, Sreekumar, Sreejith, Toffano, Zeno
Format:	Preprint
Publié:	2026
Sujets:	Quantum Physics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Complex-Valued Continuous-Variable Quantum Approximation Optimization Algorithm (CCV-QAOA)
par: Madani, Raneem, et autres
Publié: (2026)

Distributionally Robust Complex Chance-Constrained Optimization
par: Madani, Raneem, et autres
Publié: (2026)

Robust Chance Constrained Complex Zero-Sum Games
par: Madani, Raneem, et autres
Publié: (2026)

Limit Distribution Theory for Quantum Divergences
par: Sreekumar, Sreejith, et autres
Publié: (2023)

Eigenlogic and Probabilistic Inference; when Bayes meets Born
par: Dubois, François, et autres
Publié: (2025)

Quantum Maximum Likelihood Prediction via Hilbert Space Embeddings
par: Sreekumar, Sreejith, et autres
Publié: (2026)

Performance Guarantees for Quantum Neural Estimation of Entropies
par: Sreekumar, Sreejith, et autres
Publié: (2025)

Quantum Neural Estimation of Entropies
par: Goldfeld, Ziv, et autres
Publié: (2023)

Locally-Measured Rényi Divergences
par: Rippchen, Tobias, et autres
Publié: (2024)

Quantum-Assisted Trainable-Embedding Physics-Informed Neural Networks for Parabolic PDEs
par: Tran, Ban Q., et autres
Publié: (2026)

QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEs
par: Farea, Afrah, et autres
Publié: (2025)

One-shot Multiple Access Channel Simulation
par: Nema, Aditya, et autres
Publié: (2024)

Subspace Preserving Quantum Convolutional Neural Network Architectures
par: Monbroussou, Léo, et autres
Publié: (2024)

Distributed Quantum Hypothesis Testing under Zero-rate Communication Constraints
par: Sreekumar, Sreejith, et autres
Publié: (2024)

Geometric Quantum Physics Informed Neural Network
par: Tam, Wai-Hong, et autres
Publié: (2026)

Quantum Orthogonal Separable Physics-Informed Neural Networks
par: Zanotta, Pietro, et autres
Publié: (2025)

Quantum-Enhanced Convergence of Physics-Informed Neural Networks
par: Klement, Nils, et autres
Publié: (2026)

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

Physics-Informed Neural Networks for One-Dimensional Quantum Well Problems
par: Sarkar, Soumyadip
Publié: (2025)

Quantum Portfolio Optimization with Expert Analysis Evaluation
par: Innan, Nouhaila, et autres
Publié: (2025)

Achieving High-Quality Portfolio Optimization with the Variational Quantum Eigensolver
par: Wang, Anbang, et autres
Publié: (2025)

Constrained Counterdiabatic Quantum Approximate Optimization Algorithm for Portfolio Optimization
par: Falla, Jose, et autres
Publié: (2026)

Higher-Order Portfolio Optimization with Quantum Approximate Optimization Algorithm
par: Uotila, Valter, et autres
Publié: (2025)

Solving nonlinear PDEs with Quantum Neural Networks: A variational approach to the Bratu Equation
par: Cheimarios, Nikolaos
Publié: (2026)

Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
par: Wang, Huaxin, et autres
Publié: (2026)

Solving Differential Equation with Quantum-Circuit Enhanced Physics-Informed Neural Networks
par: Soni, Rachana
Publié: (2025)

Physics-Informed Neural Networks with Adaptive Constraints for Multi-Qubit Quantum Tomography
par: Feng, Changchun, et autres
Publié: (2025)

Physics-Informed Neural Networks for Gate Design using Quantum Optimal Control
par: Lauten, Sofiia, et autres
Publié: (2025)

Scaling the Variational Quantum Eigensolver for Dynamic Portfolio Optimization
par: Nodar, Álvaro, et autres
Publié: (2024)

Hamiltonian Learning via Inverse Physics-Informed Neural Networks
par: Liu, Jie, et autres
Publié: (2025)

Learning to Learn with Quantum Optimization via Quantum Neural Networks
par: Chen, Kuan-Cheng, et autres
Publié: (2025)

Forked Physics Informed Neural Networks for Coupled Systems of Differential equations
par: Wang, Zhao-Wei, et autres
Publié: (2026)

Quantum-Inspired Portfolio Optimization In The QUBO Framework
par: Lu, Ying-Chang, et autres
Publié: (2024)

A Hybrid Quantum-Classical Physics-Informed Neural Network Architecture for Solving Quantum Optimal Control Problems
par: Dehaghani, Nahid Binandeh, et autres
Publié: (2024)

Variational Quantum Physics-Informed Neural Networks for Hydrological PDE-Constrained Learning with Inherent Uncertainty Quantification
par: Hewage, Prasad Nimantha Madusanka Ukwatta, et autres
Publié: (2026)

Quantum Portfolio Optimization: An Extensive Benchmark
par: Stopfer, Eric, et autres
Publié: (2025)

Hot-Starting Quantum Portfolio Optimization
par: Schlütter, Sebastian, et autres
Publié: (2025)

Quantum Computing for Option Portfolio Analysis
par: Wu, Yusen, et autres
Publié: (2024)

Optimizer-Dependent Generalization Bound for Quantum Neural Networks
par: Zhu, Chenghong, et autres
Publié: (2025)

Enhancing Knapsack-based Financial Portfolio Optimization Using Quantum Approximate Optimization Algorithm
par: Huot, Chansreynich, et autres
Publié: (2024)