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Q-DIVER: Integrated Quantum Transfer Learning and Differentiable Quantum Architecture Search with EEG Data

arXiv 2603.28122 ↗First posted 30 Mar 2026quant-ph cs.AIcited by 0

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Abstract (arXiv)

Integrating quantum circuits into deep learning pipelines remains challenging due to heuristic design limitations. We propose Q-DIVER, a hybrid framework combining a large-scale pretrained EEG encoder (DIVER-1) with a differentiable quantum classifier. Unlike fixed-ansatz approaches, we employ Differentiable Quantum Architecture Search to autonomously discover task-optimal circuit topologies during end-to-end fine-tuning. On the PhysioNet Motor Imagery dataset, our quantum classifier achieves predictive performance comparable to classical multi-layer perceptrons (Test F1: 63.49%) while using approximately 50× fewer task-specific head parameters (2.10M vs. 105.02M). These results validate quantum transfer learning as a parameter-efficient strategy for high-dimensional biological signal processing.

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References · 18

  1. 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
  2. 2014How transferable are features in deep neural networks?cited by 1,225
  3. 2018Barren plateaus in quantum neural network training landscapescited by 630
  4. 2020The power of quantum neural networkscited by 379
  5. 2019Transfusion: Understanding Transfer Learning for Medical Imagingcited by 368
  6. 2024Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCIcited by 327
  7. 2021Generalization in quantum machine learning from few training datacited by 216
  8. 2024CBraMod: A Criss-Cross Brain Foundation Model for EEG Decodingcited by 199
  9. 2021Connecting ansatz expressibility to gradient magnitudes and barren plateauscited by 180
  10. 2019Transfer learning in hybrid classical-quantum neural networkscited by 114
  11. 2023Understanding quantum machine learning also requires rethinking generalizationcited by 49
  12. 2021A Large Collection of Real-world Pediatric Sleep Studiescited by 20
6 more
  1. 2022Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methodscited by 17
  2. 2025DIVER-1: Scaling Intracranial EEG Foundation Models for Transferable Representationscited by 5
  3. 2025Quantum Long Short-term Memory with Differentiable Architecture Searchcited by 4
  4. 2025Transfer Learning Analysis of Variational Quantum Circuitscited by 3
  5. 2025Generalization Bounds in Hybrid Quantum-Classical Machine Learning Modelscited by 3
  6. 2025Resting-state fMRI Analysis using Quantum Time-series Transformercited by 1

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