The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms
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Citations
Cites
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Monte Carlo sampling methods using Markov chains and their applications.
Hastings, W. K. (1970) · Biometrika · doi:10.1093/biomet/57.1.97 · Cited by 15,195
Phase Transitions and Critical Phenomena
(2016) · Statistical and Thermal Physics · doi:10.1201/9781439850541-13 · Cited by 11,176
Scaling concepts in polymer physics
Gordon, M. (1981) · Polymer · doi:10.1016/0032-3861(81)90183-x · Cited by 10,288
Scaling Concepts in Polymer Physics
de Gennes, P. G., & Witten, T. A. (1980) · Physics Today · doi:10.1063/1.2914118 · Cited by 9,348
Theory of dynamic critical phenomena
Hohenberg, P. C., & Halperin, B. I. (1977) · Reviews of Modern Physics · doi:10.1103/revmodphys.49.435 · Cited by 6,891
Iterative Solution of Nonlinear Equations in Several Variables
Ortega, J. M., & Rheinboldt, W. C. (2000) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9780898719468 · Cited by 6,860
Loève, M. (1963) · Andalas University Repository (Andalas University) · Cited by 5,938
Varga, R. S. (2000) · Springer Series in Computational Mathematics · doi:10.1007/978-3-642-05156-2 · Cited by 5,811
Spectral Analysis and Time Series
Preston, D. B. (1983) · Technometrics · doi:10.1080/00401706.1983.10487866 · Cited by 5,011
Cited by
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Ensemble samplers with affine invariance
Goodman, J., & Weare, J. (2010) · Communications in Applied Mathematics and Computational Science · doi:10.2140/camcos.2010.5.65 · Cited by 3,075
Nonlinear image recovery with half-quadratic regularization
Geman, D., & Yang, C. (1995) · IEEE Transactions on Image Processing · doi:10.1109/83.392335 · Cited by 1,000
Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
Papaspiliopoulos, O., & Roberts, G. O. (2008) · Biometrika · doi:10.1093/biomet/asm086 · Cited by 351
Data Analysis Recipes: Using Markov Chain Monte Carlo*
Hogg, D. W., & Foreman-Mackey, D. (2018) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/aab76e · Cited by 316
Metadata
- Authors
- Sokal, A.
- Venue
- NATO ASI Series
- Publisher
- Springer US
- Published
- 1997
- Pages
- 131-192
- ISSN
- 0258-1221 (ISSN-L)
- OpenAlex
- W1579788182
- Cited by
- 536
- References
- 63
- FWCI
- 54.88
- Type
- book chapter
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- The paper
- Sokal, A. (1997). Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms. NATO ASI Series. https://doi.org/10.1007/978-1-4899-0319-8_6
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
