:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Sulc, Antonin
Format:	Preprint
Published:	2025
Subjects:	Quantum Physics Machine Learning Computational Physics
Online Access:	https://arxiv.org/abs/2509.11911
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differentiable Logical Programming for Quantum Circuit Discovery and Optimization
by: Sulc, Antonin
Published: (2026)

Modal Logical Neural Networks
by: Sulc, Antonin
Published: (2025)

Continuous Modal Logical Neural Networks: Modal Reasoning via Stochastic Accessibility
by: Sulc, Antonin
Published: (2026)

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

Modal Logical Neural Networks for Financial AI
by: Sulc, Antonin
Published: (2026)

QCPINN: Quantum-Classical Physics-Informed Neural Networks for Solving PDEs
by: Farea, Afrah, et al.
Published: (2025)

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

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

Accurate Computation of Quantum Excited States with Neural Networks
by: Pfau, David, et al.
Published: (2023)

Provably Robust Training of Quantum Circuit Classifiers Against Parameter Noise
by: Tecot, Lucas, et al.
Published: (2025)

Quantum State Tomography using Quantum Machine Learning
by: Innan, Nouhaila, et al.
Published: (2023)

Event2Vec: A Geometric Approach to Learning Composable Representations of Event Sequences
by: Sulc, Antonin
Published: (2025)

Enhancing Quantum Variational Algorithms with Zero Noise Extrapolation via Neural Networks
by: Bhattacharjee, Subhasree, et al.
Published: (2024)

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)

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

Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics
by: Holtkamp, Yannick Marcel, et al.
Published: (2024)

CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise
by: Fu, Zhenxiao, et al.
Published: (2025)

Event Embedding of Protein Networks : Compositional Learning of Biological Function
by: Sulc, Antonin
Published: (2026)

ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation
by: Chen, Zhuo, et al.
Published: (2023)

Deep Neural Networks as the Semi-classical Limit of Topological Quantum Neural Networks: The problem of generalisation
by: Marciano, Antonino, et al.
Published: (2022)

JustQ: Automated Deployment of Fair and Accurate Quantum Neural Networks
by: Wang, Ruhan, et al.
Published: (2024)

Learning Robust Observable to Address Noise in Quantum Machine Learning
by: Khanal, Bikram, et al.
Published: (2024)

Empirical Sample Complexity of Neural Network Mixed State Reconstruction
by: Zhao, Haimeng, et al.
Published: (2023)

Active Learning with Variational Quantum Circuits for Quantum Process Tomography
by: Yang, Jiaqi, et al.
Published: (2024)

Parametric Quantum State Tomography with HyperRBMs
by: Tonner, Simon, et al.
Published: (2026)

Hybrid Quantum Neural Networks with Amplitude Encoding: Advancing Recovery Rate Predictions
by: Chen, Ying, et al.
Published: (2025)

Quantum-Classical Separations in Shallow-Circuit-Based Learning with and without Noises
by: Zhang, Zhihan, et al.
Published: (2024)

A Two-Stage Imaging Framework Combining CNN and Physics-Informed Neural Networks for Full-Inverse Tomography: A Case Study in Electrical Impedance Tomography (EIT)
by: Yang, Xuanxuan, et al.
Published: (2024)

Scalable Quantum Error Mitigation with Neighbor-Informed Learning
by: Chen, Zhenyu, et al.
Published: (2025)

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

On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
by: Gao, Nicholas, et al.
Published: (2024)

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

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

Hybrid Quantum Neural Network Advantage for Radar-Based Drone Detection and Classification in Low Signal-to-Noise Ratio
by: Malarvanan, Aiswariya Sweety
Published: (2024)

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

Fast Quantum Process Tomography via Riemannian Gradient Descent
by: Volya, Daniel, et al.
Published: (2024)

Dataset Distillation for Quantum Neural Networks
by: Phalak, Koustubh, et al.
Published: (2025)

Theory for Equivariant Quantum Neural Networks
by: Nguyen, Quynh T., et al.
Published: (2022)

Stochastic Neural Networks for Quantum Devices
by: Rosenhahn, Bodo, et al.
Published: (2026)