Trainability Beyond Linearity in Variational Quantum Objectives
Fuente:
arXiv
Saved in:
| Main Authors: | Ma, Gordon, Li, Xiufan |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Special-Unitary Parameterization for Trainable Variational Quantum Circuits
by: Chen, Kuan-Cheng, et al.
Published: (2025)
by: Chen, Kuan-Cheng, et al.
Published: (2025)
Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategies
by: Zhuang, Jun, et al.
Published: (2024)
by: Zhuang, Jun, et al.
Published: (2024)
Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression
by: Meng, Qingyu, et al.
Published: (2026)
by: Meng, Qingyu, et al.
Published: (2026)
Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms
by: Sadhu, Abhishek, et al.
Published: (2026)
by: Sadhu, Abhishek, et al.
Published: (2026)
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?
by: Wang, Samson, et al.
Published: (2021)
by: Wang, Samson, et al.
Published: (2021)
Arbitrary Polynomial Separations in Trainable Quantum Machine Learning
by: Anschuetz, Eric R., et al.
Published: (2024)
by: Anschuetz, Eric R., et al.
Published: (2024)
Characterizing Trainability of Instantaneous Quantum Polynomial Circuit Born Machines
by: Shen, Kevin, et al.
Published: (2026)
by: Shen, Kevin, et al.
Published: (2026)
Modeling Quantum Autoencoder Trainable Kernel for IoT Anomaly Detection
by: Chandrasekhar, Swathi, et al.
Published: (2025)
by: Chandrasekhar, Swathi, et al.
Published: (2025)
Quantum Graph Attention Networks: Trainable Quantum Encoders for Inductive Graph Learning
by: Faria, Arthur M., et al.
Published: (2025)
by: Faria, Arthur M., et al.
Published: (2025)
On the Design of Expressive and Trainable Pulse-based Quantum Machine Learning Models
by: Tao, Han-Xiao, et al.
Published: (2025)
by: Tao, Han-Xiao, et al.
Published: (2025)
Trainability issues in quantum policy gradients
by: Sequeira, André, et al.
Published: (2024)
by: Sequeira, André, et al.
Published: (2024)
Adaptive H-EFT-VA: A Provably Safe Trajectory Through the Trainability-Expressibility Landscape of Variational Quantum Algorithms
by: Hamid, Eyad I. B.
Published: (2026)
by: Hamid, Eyad I. B.
Published: (2026)
Enhancing Circuit Trainability with Selective Gate Activation Strategy
by: Cho, Jeihee, et al.
Published: (2025)
by: Cho, Jeihee, et al.
Published: (2025)
Sequential learning on a Tensor Network Born machine with Trainable Token Embedding
by: Hou, Wanda, et al.
Published: (2023)
by: Hou, Wanda, et al.
Published: (2023)
VQC-Based Reinforcement Learning with Data Re-uploading: Performance and Trainability
by: Coelho, Rodrigo, et al.
Published: (2024)
by: Coelho, Rodrigo, et al.
Published: (2024)
Architecture Shape Governs QNN Trainability: Jacobian Null Space Growth and Parameter Efficiency
by: Poppel, Michael, et al.
Published: (2026)
by: Poppel, Michael, et al.
Published: (2026)
Quantum Tilted Loss in Variational Optimization: Theory and Applications
by: Qiu, Yixian, et al.
Published: (2026)
by: Qiu, Yixian, et al.
Published: (2026)
Trainable Quantum Neural Network for Multiclass Image Classification with the Power of Pre-trained Tree Tensor Networks
by: Murota, Keisuke, et al.
Published: (2025)
by: Murota, Keisuke, et al.
Published: (2025)
Trainability barriers and opportunities in quantum generative modeling
by: Rudolph, Manuel S., et al.
Published: (2023)
by: Rudolph, Manuel S., et al.
Published: (2023)
Quantum Shadow Gradient Descent for Variational Quantum Algorithms
by: Heidari, Mohsen, et al.
Published: (2023)
by: Heidari, Mohsen, et al.
Published: (2023)
Resource-Efficient Variational Quantum Classifier
by: Ptáček, Petr, et al.
Published: (2025)
by: Ptáček, Petr, et al.
Published: (2025)
Barren Plateaus in Variational Quantum Computing
by: Larocca, Martin, et al.
Published: (2024)
by: Larocca, Martin, et al.
Published: (2024)
Variational Quantum Optimization with Continuous Bandits
by: Wanner, Marc, et al.
Published: (2025)
by: Wanner, Marc, et al.
Published: (2025)
Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
by: Lee, Yu-Ting, et al.
Published: (2026)
by: Lee, Yu-Ting, et al.
Published: (2026)
Active Learning with Variational Quantum Circuits for Quantum Process Tomography
by: Yang, Jiaqi, et al.
Published: (2024)
by: Yang, Jiaqi, et al.
Published: (2024)
Warm-Start Variational Quantum Policy Iteration
by: Meyer, Nico, et al.
Published: (2024)
by: Meyer, Nico, et al.
Published: (2024)
Reinforcement Learning for Variational Quantum Circuits Design
by: Foderà, Simone, et al.
Published: (2024)
by: Foderà, Simone, et al.
Published: (2024)
Spectral Bias in Variational Quantum Machine Learning
by: Duffy, Callum, et al.
Published: (2025)
by: Duffy, Callum, et al.
Published: (2025)
An Information-Minimal Geometry for Qubit-Efficient Optimization
by: Ma, Gordon, et al.
Published: (2025)
by: Ma, Gordon, et al.
Published: (2025)
Quantum Non-Linear Bandit Optimization
by: Siam, Zakaria Shams, et al.
Published: (2025)
by: Siam, Zakaria Shams, et al.
Published: (2025)
Adaptive Learning for Quantum Linear Regression
by: Carugno, Costantino, et al.
Published: (2024)
by: Carugno, Costantino, et al.
Published: (2024)
Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms
by: Lee, Junyong, et al.
Published: (2025)
by: Lee, Junyong, et al.
Published: (2025)
Comparing Classical and Quantum Variational Classifiers on the XOR Problem
by: Seilkhan, Miras, et al.
Published: (2026)
by: Seilkhan, Miras, et al.
Published: (2026)
Adaptive Observation Cost Control for Variational Quantum Eigensolvers
by: Anders, Christopher J., et al.
Published: (2025)
by: Anders, Christopher J., et al.
Published: (2025)
Noise-Induced Barren Plateaus in Variational Quantum Algorithms
by: Wang, Samson, et al.
Published: (2020)
by: Wang, Samson, et al.
Published: (2020)
Physics-Informed Bayesian Optimization of Variational Quantum Circuits
by: Nicoli, Kim A., et al.
Published: (2024)
by: Nicoli, Kim A., et al.
Published: (2024)
Fourier Analysis of Variational Quantum Circuits for Supervised Learning
by: Wiedmann, Marco, et al.
Published: (2024)
by: Wiedmann, Marco, et al.
Published: (2024)
Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers
by: Pedrielli, Samuele, et al.
Published: (2025)
by: Pedrielli, Samuele, et al.
Published: (2025)
Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances
by: Turati, Gloria, et al.
Published: (2023)
by: Turati, Gloria, et al.
Published: (2023)
Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networks
by: Jiang, Jiun-Cheng, et al.
Published: (2025)
by: Jiang, Jiun-Cheng, et al.
Published: (2025)
Similar Items
-
Special-Unitary Parameterization for Trainable Variational Quantum Circuits
by: Chen, Kuan-Cheng, et al.
Published: (2025) -
Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategies
by: Zhuang, Jun, et al.
Published: (2024) -
Geometric Preconditioning and Curriculum Optimization for Trainable Variational Quantum Regression
by: Meng, Qingyu, et al.
Published: (2026) -
Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms
by: Sadhu, Abhishek, et al.
Published: (2026) -
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms?
by: Wang, Samson, et al.
Published: (2021)