Computational Mathematics

11.5k papers and 232.4k indexed citations
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11.5k papers covering Computational Mathematics have received a total of 232.4k indexed citations since 1950. Papers on subfields are most often about the specific topic of Tensor decomposition and applications, Matrix Theory and Algorithms and Sparse and Compressive Sensing Techniques and also cover the fields of Computational Theory and Mathematics, Computational Mechanics and Radiology, Nuclear Medicine and Imaging. Papers citing papers on subfields are usually about Computational Theory and Mathematics, Computational Mechanics and Artificial Intelligence. Some of the most active scholars covering Computational Mathematics are Tamara G. Kolda, Liqun Qi, Rasmus Bro, Lieven De Lathauwer, Brett W. Bader, Ivan Oseledets, J. C. Gower, J. Douglas Carroll, Anthony Biglan and Jih-Jie Chang.

In The Last Decade

Computational Mathematics

3.1k papers receiving 25.0k citations

Fields of papers citing papers about Computational Mathematics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers covering Computational Mathematics. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers covering Computational Mathematics.

Countries where authors publish papers about Computational Mathematics

Since Specialization
Citations

This map shows the geographic impact of research in Computational Mathematics. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers about Computational Mathematics with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computational Mathematics more than expected).

Tensor Decompositions and Ap... 1970 2026 1988 2007 5.2k
  1. Tensor Decompositions and Applications (2009)
  2. Analysis of Individual Differences in Multidimensional Scaling Via an N-way Generalization of “Eckart-Young” Decomposition (1970)
  3. A Multilinear Singular Value Decomposition (2000)
  4. PARAFAC. Tutorial and applications (1997)
  5. Generalized Procrustes Analysis (1975)
  6. Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions (2011)
  7. Modern Multidimensional Scaling: Theory and Applications (2003)
  8. Tensor-Train Decomposition (2011)
  9. The characteristics of subject matter in different academic areas. (1973)
  10. How to Conduct Your Own Survey (1996)
  11. Matrix multiplication via arithmetic progressions (1990)
  12. MRtrix: Diffusion tractography in crossing fiber regions (2012)
  13. STATISTICAL ANALYSIS OF SETS OF CONGENERIC TESTS* (1969)
  14. On the Best Rank-1 and Rank-(<i>R</i><sub>1</sub> ,<i>R</i><sub>2</sub> ,. . .,<i>R<sub>N</sub></i>) Approximation of Higher-Order Tensors (2000)
  15. Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics (1977)
  16. Eigenvalues of a real supersymmetric tensor (2005)
  17. Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation (2009)
  18. A Riemannian Framework for Tensor Computing (2005)
  19. Tensor Decomposition for Signal Processing and Machine Learning (2017)
  20. Factorization strategies for third-order tensors (2010)
  21. Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis (2015)
  22. A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization (2013)
  23. Third-Order Tensors as Operators on Matrices: A Theoretical and Computational Framework with Applications in Imaging (2013)
  24. A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion (2013)
  25. Nonmetric Individual Differences Multidimensional Scaling: An Alternating Least Squares Method with Optimal Scaling Features (1977)
  26. Log‐Euclidean metrics for fast and simple calculus on diffusion tensors (2006)
  27. Updating the Inverse of a Matrix (1989)
  28. Fixed point and Bregman iterative methods for matrix rank minimization (2009)
  29. A Three-Way Model for Collective Learning on Multi-Relational Data (2011)
  30. The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: A Monte Carlo study† (2004)
  31. Relationships between subject matter characteristics and the structure and output of university departments. (1973)
  32. Issues and Advances in Segmentation Research (1978)
  33. Point of view in personal memories (1983)
  34. Processing and visualization for diffusion tensor MRI (2002)
  35. The Multilinear Engine—A Table-Driven, Least Squares Program for Solving Multilinear Problems, Including the<i>n</i>-Way Parallel Factor Analysis Model (1999)
  36. Multi‐Way Analysis with Applications in the Chemical Sciences (2004)
  37. Solving Fredholm integrals of the first kind with tensor product structure in 2 and 2.5 dimensions (2002)
  38. Most Tensor Problems Are NP-Hard (2013)
  39. Multidimensional Scaling, Tree-Fitting, and Clustering (1980)
  40. The ITensor Software Library for Tensor Network Calculations (2022)
  41. Tensor Rank and the Ill-Posedness of the Best Low-Rank Approximation Problem (2008)
  42. On the Relationship between iTem Response Theory and Factor Analysis of Discretized Variables (1987)
  43. Deterministic and Probabilistic Tractography Based on Complex Fibre Orientation Distributions (2008)
  44. The effect of filter size on VBM analyses of DT-MRI data (2005)
  45. A sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG (1999)
  46. Braided Tensor Categories (1993)
  47. A Supernodal Approach to Sparse Partial Pivoting (1999)
  48. Partialed products are interactions; partialed powers are curve components. (1978)
  49. Model Compression and Hardware Acceleration for Neural Networks: A Comprehensive Survey (2020)
  50. Towards a standardized notation and terminology in multiway analysis (2000)
  51. Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization (2018)
  52. SVD based initialization: A head start for nonnegative matrix factorization (2007)
  53. Exact Tensor Completion Using t-SVD (2016)
  54. CUR matrix decompositions for improved data analysis (2009)
  55. Studying connections in the living human brain with diffusion MRI (2008)
  56. A Novel Rule-Based Algorithm for Assigning Myocardial Fiber Orientation to Computational Heart Models (2012)
  57. Quantum Critical Scaling of the Geometric Tensors (2007)
  58. Tensorial resolution: A direct trilinear decomposition (1990)
  59. PARAFAC: Parallel factor analysis (1994)
  60. Perron-Frobenius theorem for nonnegative tensors (2008)
  61. Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination (2015)
  62. Evidence of convergent validity on the dimensions of affect. (1978)
  63. Deformable registration of diffusion tensor MR images with explicit orientation optimization (2006)
  64. Scalable tensor factorizations for incomplete data (2010)
  65. On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning (2005)
  66. A literature survey of low‐rank tensor approximation techniques (2013)
  67. Deformable Registration of Diffusion Tensor MR Images with Explicit Orientation Optimization (2005)
  68. Tensors: Geometry and Applications (2011)
  69. Cognitive functions correlate with white matter architecture in a normal pediatric population: A diffusion tensor MRI study (2005)
  70. Krylov subspace methods for solving large unsymmetric linear systems (1981)
  71. On Unifying Multi-view Self-Representations for Clustering by Tensor Multi-rank Minimization (2018)
  72. On the uniqueness of multilinear decomposition ofN-way arrays (2000)
  73. Recovering a Basic Space From a Set of Issue Scales (1998)
  74. Tensor decompositions for learning latent variable models (2014)
  75. PARAFAC2—Part I. A direct fitting algorithm for the PARAFAC2 model (1999)
  76. Regularization of Diffusion-Based Direction Maps for the Tracking of Brain White Matter Fascicles (2000)
  77. TT-cross approximation for multidimensional arrays (2009)
  78. Structured Pruning of Deep Convolutional Neural Networks (2017)
  79. Hierarchical Singular Value Decomposition of Tensors (2010)
  80. Randomized algorithms for the low-rank approximation of matrices (2007)

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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