Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning

Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning

22 January 2023

Matthias Jakobs

Nico Piatkowski

Papers citing "Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning"

11 / 11 papers shown

Title
DeQompile: quantum circuit decompilation using genetic programming for explainable quantum architecture search Shubing Xie Aritra Sarkar Sebastian Feld 27 0 0 11 Apr 2025
Interpretable Machine Learning in Physics: A Review Sebastian Johann Wetzel Seungwoong Ha Raban Iten Miriam Klopotek Ziming Liu AI4CE 75 0 0 30 Mar 2025
Quantum Artificial Intelligence: A Brief Survey Matthias Klusch Jorg Lassig Daniel Mussig A. Macaluso Frank K. Wilhelm 33 2 0 20 Aug 2024
Quantum Gradient Class Activation Map for Model Interpretability Hsin-Yi Lin Huan-Hsin Tseng Samuel Yen-Chi Chen Shinjae Yoo FAtt 26 4 0 12 Aug 2024
Feature Importance and Explainability in Quantum Machine Learning Luke Power Krishnendu Guha FAtt VLM 16 5 0 14 May 2024
VIOLET: Visual Analytics for Explainable Quantum Neural Networks Shaolun Ruan Zhiding Liang Qian-Guo Guan Paul Griffin Xiaolin Wen Yanna Lin Yong Wang 32 1 0 23 Dec 2023
On the Interpretability of Quantum Neural Networks Lirande Pira C. Ferrie FAtt 27 14 0 22 Aug 2023
Towards interpretable quantum machine learning via single-photon quantum walks Fulvio Flamini Marius Krumm Lukas J. Fiderer Thomas Müller H. Briegel 16 6 0 31 Jan 2023
The complexity of quantum support vector machines Gian Gentinetta Arne Thomsen David Sutter Stefan Woerner 29 40 0 28 Feb 2022
Systematic Literature Review: Quantum Machine Learning and its applications David Peral García Juan Cruz-Benito Francisco José García-Penalvo 30 118 0 11 Jan 2022
Connecting ansatz expressibility to gradient magnitudes and barren plateaus Zoë Holmes Kunal Sharma M. Cerezo Patrick J. Coles 118 420 0 06 Jan 2021