Saved in:
| Main Authors: | Klement, Nils, Eyring, Veronika, Schwabe, Mierk |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.15046 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models
by: Pastori, Lorenzo, et al.
Published: (2025)
by: Pastori, Lorenzo, et al.
Published: (2025)
Quantum Machine Learning for Climate Modelling
by: Schwabe, Mierk, et al.
Published: (2025)
by: Schwabe, Mierk, et al.
Published: (2025)
Fisher Information, Training and Bias in Fourier Regression Models
by: Pastori, Lorenzo, et al.
Published: (2025)
by: Pastori, Lorenzo, et al.
Published: (2025)
Quantum Bayesian Optimization for the Automatic Tuning of Lorenz-96 as a Surrogate Climate Model
by: Christiansen, Paul J., et al.
Published: (2025)
by: Christiansen, Paul J., et al.
Published: (2025)
Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON
by: Heuer, Helge, et al.
Published: (2023)
by: Heuer, Helge, et al.
Published: (2023)
Interpretable Neural Networks to Predict Momentum Fluxes of Orographic Gravity Waves
by: Haslauer, Elias, et al.
Published: (2026)
by: Haslauer, Elias, et al.
Published: (2026)
Opportunities and challenges of quantum computing for climate modelling
by: Schwabe, Mierk, et al.
Published: (2025)
by: Schwabe, Mierk, et al.
Published: (2025)
Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model
by: Heuer, Helge, et al.
Published: (2025)
by: Heuer, Helge, et al.
Published: (2025)
Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties with Deep Learning Multi-Member and Stochastic Parameterizations
by: Behrens, Gunnar, et al.
Published: (2024)
by: Behrens, Gunnar, et al.
Published: (2024)
Dynamical effects in fluid complex plasmas
by: Schwabe, Mierk
Published: (2009)
by: Schwabe, Mierk
Published: (2009)
Particle-resolved study of the onset of turbulence
by: Joshi, Eshita, et al.
Published: (2023)
by: Joshi, Eshita, et al.
Published: (2023)
Solving Differential Equation with Quantum-Circuit Enhanced Physics-Informed Neural Networks
by: Soni, Rachana
Published: (2025)
by: Soni, Rachana
Published: (2025)
Geometric Quantum Physics Informed Neural Network
by: Tam, Wai-Hong, et al.
Published: (2026)
by: Tam, Wai-Hong, et al.
Published: (2026)
Quantum Orthogonal Separable Physics-Informed Neural Networks
by: Zanotta, Pietro, et al.
Published: (2025)
by: Zanotta, Pietro, et al.
Published: (2025)
Quantum Noise Tomography with Physics-Informed Neural Networks
by: Sulc, Antonin
Published: (2025)
by: Sulc, Antonin
Published: (2025)
Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi-Member and Stochastic Parameterizations
by: Behrens, Gunnar, et al.
Published: (2025)
by: Behrens, Gunnar, et al.
Published: (2025)
Learning PDEs for Portfolio Optimization with Quantum Physics-Informed Neural Networks
by: Wang, Letao, et al.
Published: (2026)
by: Wang, Letao, et al.
Published: (2026)
Physics-Informed Neural Networks for One-Dimensional Quantum Well Problems
by: Sarkar, Soumyadip
Published: (2025)
by: Sarkar, Soumyadip
Published: (2025)
Quantum-Assisted Trainable-Embedding Physics-Informed Neural Networks for Parabolic PDEs
by: Tran, Ban Q., et al.
Published: (2026)
by: Tran, Ban Q., et al.
Published: (2026)
Physics-Informed Neural Networks with Adaptive Constraints for Multi-Qubit Quantum Tomography
by: Feng, Changchun, et al.
Published: (2025)
by: Feng, Changchun, et al.
Published: (2025)
Physics-Informed Neural Networks for Gate Design using Quantum Optimal Control
by: Lauten, Sofiia, et al.
Published: (2025)
by: Lauten, Sofiia, et al.
Published: (2025)
AQ-PINNs: Attention-Enhanced Quantum Physics-Informed Neural Networks for Carbon-Efficient Climate Modeling
by: Dutta, Siddhant, et al.
Published: (2024)
by: Dutta, Siddhant, et al.
Published: (2024)
Scalable Quantum Error Mitigation with Physically Informed Graph Neural Networks
by: Wang, Huaxin, et al.
Published: (2026)
by: Wang, Huaxin, et al.
Published: (2026)
QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEs
by: Farea, Afrah, et al.
Published: (2025)
by: Farea, Afrah, et al.
Published: (2025)
A Hybrid Quantum-Classical Physics-Informed Neural Network Architecture for Solving Quantum Optimal Control Problems
by: Dehaghani, Nahid Binandeh, et al.
Published: (2024)
by: Dehaghani, Nahid Binandeh, et al.
Published: (2024)
QINNs: Quantum-Informed Neural Networks
by: Bal, Aritra, et al.
Published: (2025)
by: Bal, Aritra, et al.
Published: (2025)
Addressing the Non-perturbative Regime of the Quantum Anharmonic Oscillator by Physics-Informed Neural Networks
by: Brevi, Lorenzo, et al.
Published: (2024)
by: Brevi, Lorenzo, et al.
Published: (2024)
Physics-Informed Neural Networks for Maximizing Quantum Fisher Information in Time-Dependent Many-Body Systems
by: Ferrer-Sánchez, Antonio, et al.
Published: (2026)
by: Ferrer-Sánchez, Antonio, et al.
Published: (2026)
A Tutorial on the Use of Physics-Informed Neural Networks to Compute the Spectrum of Quantum Systems
by: Brevi, Lorenzo, et al.
Published: (2024)
by: Brevi, Lorenzo, et al.
Published: (2024)
Forked Physics Informed Neural Networks for Coupled Systems of Differential equations
by: Wang, Zhao-Wei, et al.
Published: (2026)
by: Wang, Zhao-Wei, 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)
by: Hewage, Prasad Nimantha Madusanka Ukwatta, et al.
Published: (2026)
Physics-Constrained Adaptive Flow Matching for Climate Downscaling
by: Debeire, Kevin, et al.
Published: (2026)
by: Debeire, Kevin, et al.
Published: (2026)
Quantum Physics-Informed Neural Networks for Maxwell's Equations: Circuit Design, "Black Hole" Barren Plateaus Mitigation, and GPU Acceleration
by: Chen, Ziv, et al.
Published: (2025)
by: Chen, Ziv, et al.
Published: (2025)
Graph Neural Networks for Enhanced Decoding of Quantum LDPC Codes
by: Gong, Anqi, et al.
Published: (2023)
by: Gong, Anqi, et al.
Published: (2023)
Quantum Suicide in Many-Worlds Implies P=NP
by: Baumann, Veronika, et al.
Published: (2026)
by: Baumann, Veronika, et al.
Published: (2026)
Hamiltonian Learning via Inverse Physics-Informed Neural Networks
by: Liu, Jie, et al.
Published: (2025)
by: Liu, Jie, et al.
Published: (2025)
Next-Generation Quantum Neural Networks: Enhancing Efficiency, Security, and Privacy
by: Innan, Nouhaila, et al.
Published: (2025)
by: Innan, Nouhaila, et al.
Published: (2025)
Enhanced Squeezing and Faster Metrology from Layered Quantum Neural Networks
by: Gutierrez, Nickholas, et al.
Published: (2025)
by: Gutierrez, Nickholas, et al.
Published: (2025)
Quantum Neural Physics: Solving Partial Differential Equations on Quantum Simulators using Quantum Convolutional Neural Networks
by: Zhai, Jucai, et al.
Published: (2026)
by: Zhai, Jucai, et al.
Published: (2026)
Towards Physically Consistent Deep Learning For Climate Model Parameterizations
by: Kühbacher, Birgit, et al.
Published: (2024)
by: Kühbacher, Birgit, et al.
Published: (2024)
Similar Items
-
Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models
by: Pastori, Lorenzo, et al.
Published: (2025) -
Quantum Machine Learning for Climate Modelling
by: Schwabe, Mierk, et al.
Published: (2025) -
Fisher Information, Training and Bias in Fourier Regression Models
by: Pastori, Lorenzo, et al.
Published: (2025) -
Quantum Bayesian Optimization for the Automatic Tuning of Lorenz-96 as a Surrogate Climate Model
by: Christiansen, Paul J., et al.
Published: (2025) -
Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON
by: Heuer, Helge, et al.
Published: (2023)