doi:10.1016/0010-4655(90)90186-5
H.-O. Heuer, A fast vectorized fortran 77 program for the monte carlo simulation of the three-dimensional ising system , Computer Physics Communications 59 (2) (1990) 387 – 398 · 1990
Cited alongside, same era.
C. J. Geyer, Markov chain monte carlo maximum likelihood, in: E. M. Keramidas (Ed.), Computing Science and Statistics: 23rd Symposium on the Interface, Interface Foundation, Fairfax Station, 1991, 1991, pp. 156–163
1991
Cited alongside, same era.
doi:10.1007/BF01053609
H. Rieger, Fast vectorized algorithm for the monte carlo simulation of the random field ising model , Journal of Statistical Physics 70 (3-4) (1993) 1063–1073 · 1993
Cited alongside, same era.
T. Fischer, H. Lüthi, W. Petersen, A New Optimization Technique for Artificial Neural Networks Used in Prediction of Force Constants of Large Molecules , IPS research report, IPS, Interdisciplinary Project Center for Supercomputing, ETH-Zentrum, 1994. URL http://books.google.ch/books?id=d-onPwAACAAJ
1994
Cited alongside, same era.
doi:10.1142/S0129183103004498
J. J. Moreno, H. G. Katzgraber, A. K. Hartmann, Finding low-temperature states with parallel tempering, simulated annealing and simple monte carlo , International Journal of Modern Physics C 14 (03) (2003) 285–302 · 2003
Cited alongside, same era.
arXiv:arXiv:0804.4457
Original
H. Neven, G. Rose, W. G. Macready, Image recognition with an adiabatic quantum computer i. mapping to quadratic unconstrained binary optimization (2008) · 2008
Cited alongside, same era.