Skip to content
Universidad del Mar SIBUMAR Descubridor Institucional UMAR
  • Inicio
  • Búsqueda avanzada
  • Explorar
  • Login
    • English
    • Deutsch
    • Español
    • Français
    • Italiano
Advanced
  • Quantum LEGO Learning: A Modular Design Principle for Hybrid Artificial Intelligence
Cover Image

Quantum LEGO Learning: A Modular Design Principle for Hybrid Artificial Intelligence

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Qi, Jun, Yang, Chao-Han Huck, Chen, Pin-Yu, Hsieh, Min-Hsiu, Zenil, Hector, Tegner, Jesper
Format: Preprint
Published: 2026
Subjects:
Machine Learning
Quantum Physics
Online Access:
Acceder al recurso
Tags: Add Tag
No Tags, Be the first to tag this record!
  • Cite this
  • Text this
  • Email this
  • Print
  • Export Record
    • Export to RefWorks
    • Export to EndNoteWeb
    • Export to EndNote
  • Save to List
  • Permanent link
  • Holdings
  • Description
  • Comments
  • Similar Items
  • Staff View

Internet

https://arxiv.org/abs/2601.21780

Similar Items

  • Leveraging Pre-Trained Neural Networks to Enhance Machine Learning with Variational Quantum Circuits
    by: Qi, Jun, et al.
    Published: (2024)
  • Pre-training Tensor-Train Networks Facilitates Machine Learning with Variational Quantum Circuits
    by: Qi, Jun, et al.
    Published: (2023)
  • VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning
    by: Qi, Jun, et al.
    Published: (2025)
  • Random-Matrix-Induced Simplicity Bias in Over-parameterized Variational Quantum Circuits
    by: Qi, Jun, et al.
    Published: (2026)
  • TensorHyper-VQC: A Tensor-Train-Guided Hypernetwork for Robust and Scalable Variational Quantum Computing
    by: Qi, Jun, et al.
    Published: (2025)
Universidad del Mar
Universidad del MarSistema Bibliotecario de la Universidad del MarDescubridor Institucional UMARImplementación y desarrollo: Mtro. Carlos Alonso Albores Pérez
InicioBúsqueda avanzadaExplorar
Visitas al Descubridor: 33,245© 2026 Universidad del Mar