Overfitting in quantum machine learning and entangling dropout

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Overfitting in quantum machine learning and entangling dropout

Quantum Machine Intelligence (QMI), 2022

23 May 2022

Masahiro Kobayashi

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Papers citing "Overfitting in quantum machine learning and entangling dropout"

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Title
Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning Maximilian Wendlinger Kilian Tscharke Pascal Debus UQCV AI4CE 147 1 0 20 Jul 2025
Addressing the Current Challenges of Quantum Machine Learning through Multi-Chip Ensembles Junghoon Justin Park Jiook Cha Samuel Yen-Chi Chen Huan-Hsin Tseng Shinjae Yoo 425 3 0 13 May 2025
Training-efficient density quantum machine learning Brian Coyle El Amine Cherrat Nishant Jain Natansh Mathur Snehal Raj Skander Kazdaghli Iordanis Kerenidis 317 10 0 30 May 2024
Graph Neural Networks for Parameterized Quantum Circuits Expressibility EstimationInternational Conference on Quantum Computing and Engineering (QCE), 2024 Shammi Aktar Andreas Bartschi Diane Oyen S. Eidenbenz Abdel-Hameed A. Badawy 191 4 0 13 May 2024
Permutation-equivariant quantum convolutional neural networks Sreetama Das Filippo Caruso 219 3 0 28 Apr 2024
A Post-Training Approach for Mitigating Overfitting in Quantum Convolutional Neural Networks Aakash Ravindra Shinde Charu Jain A. Kalev 248 3 0 04 Sep 2023
Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine LearningIEEE Transactions on Quantum Engineering (TQE), 2023 Sangwoo Park Osvaldo Simeone 208 20 0 06 Apr 2023