A method for quantifying the generalization capabilities of generative models for solving Ising models

6 May 2024

Papers citing "A method for quantifying the generalization capabilities of generative models for solving Ising models"

10 / 10 papers shown

Title
Do Quantum Circuit Born Machines Generalize? Kaitlin Gili Mohamed Hibat-Allah M. Mauri C. Ballance A. Perdomo-Ortiz 132 31 0 27 Jul 2022
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation Qinghua Zhou Alexander N. Gorban Evgeny M. Mirkes Jonathan Bac A. Zinovyev I. Tyukin 40 2 0 30 Mar 2022
On Evaluation Metrics for Graph Generative Models Rylee Thompson Boris Knyazev Elahe Ghalebi Jungtaek Kim Graham W. Taylor EGVM 101 43 0 24 Jan 2022
Variational Neural Annealing Mohamed Hibat-Allah E. Inack R. Wiersema R. Melko Juan Carrasquilla DRL 99 83 0 25 Jan 2021
Neural Architecture Search without Training J. Mellor Jack Turner Amos Storkey Elliot J. Crowley 65 384 0 08 Jun 2020
How Well Do WGANs Estimate the Wasserstein Metric? Anton Mallasto Guido Montúfar Augusto Gerolin 48 25 0 09 Oct 2019
Solving Statistical Mechanics Using Variational Autoregressive Networks Dian Wu Lei Wang Pan Zhang 102 186 0 27 Sep 2018
On the ability of neural nets to express distributions Holden Lee Rong Ge Tengyu Ma Andrej Risteski Sanjeev Arora BDL 86 84 0 22 Feb 2017
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 679 29,183 0 09 Sep 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 486 2,579 0 25 Jan 2016