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Foundations of Data Science invites submissions focusing on advances in mathematical, statistical, and computational methods for data science. Results should significantly advance current understanding of data science, by algorithm development, analysis, and/or computational implementation which demonstrates behavior and applicability of the algorithm. Fields covered by the journal include, but are not limited to Bayesian Statistics, High Performance Computing, Inverse Problems, Data Assimilation, Machine Learning, Optimization, Topological Data Analysis, Spatial Statistics, Nonparametric Statistics, Uncertainty Quantification, and Data Centric Engineering. Expository and review articles are welcome. Papers which focus on applications in science and engineering are also encouraged, however the method(s) used should be applicable outside of one specific application domain.

  • AIMS is a member of COPE. All AIMS journals adhere to the publication ethics and malpractice policies outlined by COPE.
  • Publishes 4 issues a year in March, June, September and December.
  • Publishes online only.
  • Archived in Portico and CLOCKSS.
  • FoDS is a publication of the American Institute of Mathematical Sciences. All rights reserved.

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Editorial
Ajay Jasra, Kody J. H. Law and Vasileios Maroulas
2019, 1(1) : ⅰ-ⅲ doi: 10.3934/fods.20191i +[Abstract](304) +[HTML](190) +[PDF](81.25KB)
Consistent manifold representation for topological data analysis
Tyrus Berry and Timothy Sauer
2019, 1(1) : 1-38 doi: 10.3934/fods.2019001 +[Abstract](476) +[HTML](207) +[PDF](3141.49KB)
Approximate Bayesian inference for geostatistical generalised linear models
Evangelos Evangelou
2019, 1(1) : 39-60 doi: 10.3934/fods.2019002 +[Abstract](640) +[HTML](174) +[PDF](1121.17KB)
Particle filters for inference of high-dimensional multivariate stochastic volatility models with cross-leverage effects
Yaxian Xu and Ajay Jasra
2019, 1(1) : 61-85 doi: 10.3934/fods.2019003 +[Abstract](436) +[HTML](222) +[PDF](935.96KB)
Combinatorial Hodge theory for equitable kidney paired donation
Joshua L. Mike and Vasileios Maroulas
2019, 1(1) : 87-101 doi: 10.3934/fods.2019004 +[Abstract](539) +[HTML](231) +[PDF](1089.46KB)
Accelerating Metropolis-Hastings algorithms by Delayed Acceptance
Marco Banterle, Clara Grazian, Anthony Lee and Christian P. Robert
2019, 0(0) : 0-0 doi: 10.3934/fods.2019005 +[Abstract](270) +[HTML](166) +[PDF](660.16KB) Cited By(0)
Consistent manifold representation for topological data analysis
Tyrus Berry and Timothy Sauer
2019, 1(1) : 1-38 doi: 10.3934/fods.2019001 +[Abstract](476) +[HTML](207) +[PDF](3141.49KB) Cited By(0)
Editorial
Ajay Jasra, Kody J. H. Law and Vasileios Maroulas
2019, 1(1) : ⅰ-ⅲ doi: 10.3934/fods.20191i +[Abstract](304) +[HTML](190) +[PDF](81.25KB) Cited By(0)
Combinatorial Hodge theory for equitable kidney paired donation
Joshua L. Mike and Vasileios Maroulas
2019, 1(1) : 87-101 doi: 10.3934/fods.2019004 +[Abstract](539) +[HTML](231) +[PDF](1089.46KB) Cited By(0)
Flexible online multivariate regression with variational Bayes and the matrix-variate Dirichlet process
Victor Meng Hwee Ong, David J. Nott, Taeryon Choi and Ajay Jasra
2019, 0(0) : 0-0 doi: 10.3934/fods.2019006 +[Abstract](66) +[HTML](34) +[PDF](1004.28KB) Cited By(0)
Estimation and uncertainty quantification for the output from quantum simulators
Ryan Bennink, Ajay Jasra, Kody J. H. Law and Pavel Lougovski
2019, 0(0) : 0-0 doi: 10.3934/fods.2019007 +[Abstract](115) +[HTML](50) +[PDF](854.04KB) Cited By(0)
Approximate Bayesian inference for geostatistical generalised linear models
Evangelos Evangelou
2019, 1(1) : 39-60 doi: 10.3934/fods.2019002 +[Abstract](640) +[HTML](174) +[PDF](1121.17KB) Cited By(0)
Particle filters for inference of high-dimensional multivariate stochastic volatility models with cross-leverage effects
Yaxian Xu and Ajay Jasra
2019, 1(1) : 61-85 doi: 10.3934/fods.2019003 +[Abstract](436) +[HTML](222) +[PDF](935.96KB) Cited By(0)
Particle filters for inference of high-dimensional multivariate stochastic volatility models with cross-leverage effects
Yaxian Xu and Ajay Jasra
2019, 1(1) : 61-85 doi: 10.3934/fods.2019003 +[Abstract](436) +[HTML](222) +[PDF](935.96KB) PDF Downloads(59)
Consistent manifold representation for topological data analysis
Tyrus Berry and Timothy Sauer
2019, 1(1) : 1-38 doi: 10.3934/fods.2019001 +[Abstract](476) +[HTML](207) +[PDF](3141.49KB) PDF Downloads(55)
Approximate Bayesian inference for geostatistical generalised linear models
Evangelos Evangelou
2019, 1(1) : 39-60 doi: 10.3934/fods.2019002 +[Abstract](640) +[HTML](174) +[PDF](1121.17KB) PDF Downloads(44)
Accelerating Metropolis-Hastings algorithms by Delayed Acceptance
Marco Banterle, Clara Grazian, Anthony Lee and Christian P. Robert
2019, 0(0) : 0-0 doi: 10.3934/fods.2019005 +[Abstract](270) +[HTML](166) +[PDF](660.16KB) PDF Downloads(28)
Editorial
Ajay Jasra, Kody J. H. Law and Vasileios Maroulas
2019, 1(1) : ⅰ-ⅲ doi: 10.3934/fods.20191i +[Abstract](304) +[HTML](190) +[PDF](81.25KB) PDF Downloads(27)
Combinatorial Hodge theory for equitable kidney paired donation
Joshua L. Mike and Vasileios Maroulas
2019, 1(1) : 87-101 doi: 10.3934/fods.2019004 +[Abstract](539) +[HTML](231) +[PDF](1089.46KB) PDF Downloads(22)
Estimation and uncertainty quantification for the output from quantum simulators
Ryan Bennink, Ajay Jasra, Kody J. H. Law and Pavel Lougovski
2019, 0(0) : 0-0 doi: 10.3934/fods.2019007 +[Abstract](115) +[HTML](50) +[PDF](854.04KB) PDF Downloads(14)
Flexible online multivariate regression with variational Bayes and the matrix-variate Dirichlet process
Victor Meng Hwee Ong, David J. Nott, Taeryon Choi and Ajay Jasra
2019, 0(0) : 0-0 doi: 10.3934/fods.2019006 +[Abstract](66) +[HTML](34) +[PDF](1004.28KB) PDF Downloads(6)

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