Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels

26 March 2023

Papers citing "Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels"

8 / 8 papers shown

Title
Quantum-PEFT: Ultra parameter-efficient fine-tuning Toshiaki Koike-Akino F. Tonin Yongtao Wu Frank Zhengqing Wu Leyla Naz Candogan Volkan Cevher MQ 180 5 0 07 Mar 2025
Exponentially Many Local Minima in Quantum Neural Networks Xuchen You Xiaodi Wu 87 54 0 06 Oct 2021
Theory of overparametrization in quantum neural networks Martín Larocca Nathan Ju Diego García-Martín Patrick J. Coles M. Cerezo 74 191 0 23 Sep 2021
Power of data in quantum machine learning Hsin-Yuan Huang Michael Broughton Masoud Mohseni Ryan Babbush Sergio Boixo Hartmut Neven Jarrod R. McClean 69 645 0 03 Nov 2020
Quantum Wasserstein Generative Adversarial Networks Shouvanik Chakrabarti Yiming Huang Tongyang Li Soheil Feizi Xiaodi Wu GNN GAN 71 84 0 31 Oct 2019
On the Inductive Bias of Neural Tangent Kernels A. Bietti Julien Mairal 69 259 0 29 May 2019
Barren plateaus in quantum neural network training landscapes Jarrod R. McClean Sergio Boixo V. Smelyanskiy Ryan Babbush Hartmut Neven 64 1,816 0 29 Mar 2018
On the Computational Efficiency of Training Neural Networks Roi Livni Shai Shalev-Shwartz Ohad Shamir 141 480 0 05 Oct 2014