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Showing below up to 334 results in range #1 to #334.
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- Help (12:37, 25 March 2015)
- Back substitution (14:21, 30 July 2015)
- Open Encyclopedia of Parallel Algorithmic Features (22:46, 3 September 2015)
- Elimination method, pointwise version (17:41, 1 March 2016)
- Glossary (11:37, 18 June 2016)
- Description of algorithm properties and structure (10:23, 24 October 2017)
- Methods for solving tridiagonal SLAEs (15:32, 9 November 2017)
- Householder (reflections) method for the QR decomposition of a matrix (13:42, 2 March 2018)
- LU decomposition using Gaussian elimination without pivoting (11:23, 5 March 2018)
- LU decomposition using Gaussian elimination with pivoting (11:40, 5 March 2018)
- All Pairs Shortest Path (APSP) (17:06, 6 March 2018)
- Transitive closure of a directed graph (17:06, 6 March 2018)
- Search for isomorphic subgraphs (17:07, 6 March 2018)
- Graph connectivity (17:07, 6 March 2018)
- Finding maximal flow in a transportation network (17:08, 6 March 2018)
- Assignment problem (17:08, 6 March 2018)
- Pairwise summation (14:11, 14 March 2018)
- Parallel prefix scan algorithm using pairwise summation (14:14, 14 March 2018)
- Uniform norm of a vector: Real version, serial-parallel variant (14:18, 14 March 2018)
- Fast Fourier transform for powers-of-two (14:22, 14 March 2018)
- Dense matrix multiplication (14:26, 14 March 2018)
- Matrix decomposition problem (14:29, 14 March 2018)
- Triangular decompositions (14:31, 14 March 2018)
- Gaussian elimination (finding the LU decomposition) (14:34, 14 March 2018)
- Compact scheme for Gaussian elimination and its modifications: Tridiagonal matrix (14:40, 14 March 2018)
- Serial-parallel algorithm for the LU decomposition of a tridiagonal matrix (14:49, 14 March 2018)
- Gaussian elimination with column pivoting (14:51, 14 March 2018)
- Gaussian elimination with row pivoting (14:54, 14 March 2018)
- Gaussian elimination with diagonal pivoting (14:55, 14 March 2018)
- Gaussian elimination with complete pivoting (14:56, 14 March 2018)
- Householder (reflections) method for the QR decomposition of a square matrix, real point-wise version (14:58, 14 March 2018)
- Classical orthogonalization method (14:59, 14 March 2018)
- Orthogonalization method with reorthogonalization (15:01, 14 March 2018)
- Reducing matrices to compact forms (15:04, 14 March 2018)
- Unitary reductions to Hessenberg form (15:05, 14 March 2018)
- Classical point-wise Householder (reflections) method for reducing a matrix to Hessenberg form (15:06, 14 March 2018)
- Unitary reductions to tridiagonal form (15:08, 14 March 2018)
- Eigenvalue decomposition (finding eigenvalues and eigenvectors) (15:13, 14 March 2018)
- Householder (reflections) reduction of a matrix to bidiagonal form (15:15, 14 March 2018)
- Singular value decomposition (finding singular values and singular vectors) (15:16, 14 March 2018)
- The dqds algorithm for calculating singular values of bidiagonal matrices (15:18, 14 March 2018)
- Thomas algorithm (15:25, 14 March 2018)
- Repeated Thomas algorithm, pointwise version (15:27, 14 March 2018)
- Stone doubling algorithm (15:29, 14 March 2018)
- Stone doubling algorithm for solving bidiagonal SLAEs (15:32, 14 March 2018)
- Serial-parallel method for solving tridiagonal matrices based on the LU decomposition and backward substitutions (15:34, 14 March 2018)
- Repeated two-sided Thomas algorithm, pointwise version (15:36, 14 March 2018)
- Complete cyclic reduction (15:37, 14 March 2018)
- Block Thomas algorithm (15:40, 14 March 2018)
- Two-sided Thomas algorithm, block variant (15:42, 14 March 2018)
- High Performance Conjugate Gradient (HPCG) benchmark (15:43, 14 March 2018)
- Biconjugate gradient stabilized method (BiCGStab) (15:45, 14 March 2018)
- Kaczmarz's algorithm (15:46, 14 March 2018)
- QR algorithm (15:48, 14 March 2018)
- QR algorithm as implemented in SCALAPACK (15:50, 14 March 2018)
- Hessenberg QR algorithm as implemented in SCALAPACK (15:52, 14 March 2018)
- Symmetric QR algorithm as implemented in SCALAPACK (15:54, 14 March 2018)
- QR algorithm for complex Hermitian matrices as implemented in SCALAPACK (15:57, 14 March 2018)
- Householder (reflections) method for reducing a complex Hermitian matrix to symmetric tridiagonal form (16:00, 14 March 2018)
- The Jacobi (rotations) method for solving the symmetric eigenvalue problem (16:05, 14 March 2018)
- The classical Jacobi (rotations) method with pivoting for symmetric matrices (16:07, 14 March 2018)
- Serial Jacobi (rotations) method for symmetric matrices (16:08, 14 March 2018)
- Serial Jacobi (rotations) method with thresholds for symmetric matrices (16:10, 14 March 2018)
- Lanczos algorithm in exact algorithm (without reorthogonalization) (16:12, 14 March 2018)
- Jacobi (rotations) method for finding singular values (16:13, 14 March 2018)
- Binary search: Finding the position of a target value within a sorted array (16:17, 14 March 2018)
- Depth-first search (DFS) (16:38, 14 March 2018)
- Johnson's algorithm (16:42, 14 March 2018)
- Longest shortest path (16:45, 14 March 2018)
- Kruskal's algorithm (16:46, 14 March 2018)
- Prim's algorithm (16:47, 14 March 2018)
- GHS algorithm (16:49, 14 March 2018)
- Ullman's algorithm (16:50, 14 March 2018)
- VF2 algorithm (16:51, 14 March 2018)
- Disjoint set union (16:54, 14 March 2018)
- Tarjan's strongly connected components algorithm (16:55, 14 March 2018)
- Tarjan's biconnected components algorithm (16:57, 14 March 2018)
- Tarjan's algorithm for finding the bridges of a graph (16:58, 14 March 2018)
- Vertex connectivity of a graph (16:59, 14 March 2018)
- Gabow's edge connectivity algorithm (17:00, 14 March 2018)
- Ford–Fulkerson algorithm (17:01, 14 March 2018)
- Preflow-Push algorithm (17:04, 14 March 2018)
- Finding minimal-cost flow in a transportation network (17:06, 14 March 2018)
- Hungarian algorithm (17:08, 14 March 2018)
- Auction algorithm (17:09, 14 March 2018)
- Hopcroft–Karp algorithm (17:10, 14 March 2018)
- Two-qubit transform of a state vector (17:12, 14 March 2018)
- K-means clustering (17:14, 14 March 2018)
- Face recognition (17:20, 14 March 2018)
- Stochastic dual dynamic programming (SDDP) (17:23, 14 March 2018)
- Newton's method for systems of nonlinear equations (17:24, 14 March 2018)
- Cubature rules (17:26, 14 March 2018)
- Numerical quadrature (cubature) rules on an interval (for a multidimensional cube) (17:28, 14 March 2018)
- Meet-in-the-middle attack (17:30, 14 March 2018)
- Householder (reflections) method for reducing of a matrix to Hessenberg form (13:03, 15 March 2018)
- Algorithm classification (13:06, 15 March 2018)
- QR decomposition of dense nonsingular matrices (16:14, 16 March 2018)
- Gaussian elimination, compact scheme for tridiagonal matrices and its modifications (16:41, 16 March 2018)
- Gaussian elimination, compact scheme for tridiagonal matrices, serial variant (16:53, 16 March 2018)
- Orthogonalization method (16:58, 16 March 2018)
- Triangular decomposition of a Gram matrix (17:02, 16 March 2018)
- QR decomposition methods for dense Hessenberg matrices (17:09, 16 March 2018)
- Unitary-triangular factorizations (17:11, 16 March 2018)
- Шаблон:Buttonlinkimp (14:20, 19 June 2018)
- Construction of the minimum spanning tree (MST) (14:56, 19 June 2018)
- Shiloach-Vishkin algorithm for finding the connected components (15:03, 19 June 2018)
- Single Source Shortest Path (SSSP) (17:48, 19 June 2018)
- Cholesky method (13:01, 10 August 2018)
- Участник:VolkovNikita94 (21:58, 10 May 2019)
- About project (16:30, 11 September 2019)
- Givens (rotations) method for the QR decomposition of a matrix (10:14, 6 April 2020)
- Cooley-Tukey, scalability (16:24, 1 July 2022)
- Cooley–Tukey Fast Fourier Transform, radix-2 case (16:45, 1 July 2022)
- BFS, C++, Boost Graph Library (10:42, 2 July 2022)
- BFS, C++, MPI, Boost Graph Library (10:44, 2 July 2022)
- BFS, GAP (10:48, 2 July 2022)
- BFS, Java, WebGraph (10:51, 2 July 2022)
- BFS, Python, NetworkX (10:57, 2 July 2022)
- BFS, Python/C++, NetworKit (11:01, 2 July 2022)
- Dijkstra, C++, Boost Graph Library (10:03, 4 July 2022)
- Dijkstra, Python (10:26, 4 July 2022)
- Dijkstra, Python/C++ (10:30, 4 July 2022)
- Dijkstra, C++, MPI: Parallel Boost Graph Library, 1 (10:36, 4 July 2022)
- Dijkstra, C++, MPI: Parallel Boost Graph Library, 2 (10:39, 4 July 2022)
- Dijkstra, locality (11:00, 4 July 2022)
- Dijkstra, Google (11:10, 4 July 2022)
- Dijkstra's algorithm (15:02, 4 July 2022)
- Bellman-Ford, C++, Boost Graph Library (15:17, 4 July 2022)
- Bellman-Ford, Python, NetworkX (15:21, 4 July 2022)
- Bellman-Ford, Java, JGraphT (15:27, 4 July 2022)
- Bellman-Ford, OpenMP, Stinger (15:35, 4 July 2022)
- Bellman-Ford, Nvidia nvGraph (15:40, 4 July 2022)
- Bellman-Ford, MPI, Graph500 (15:47, 4 July 2022)
- BFS, Ligra (15:52, 4 July 2022)
- Bellman-Ford, Ligra (15:54, 4 July 2022)
- Bellman-Ford, locality (16:11, 4 July 2022)
- Bellman-Ford, scalability (16:25, 4 July 2022)
- BFS, MPI, Graph500 (16:29, 4 July 2022)
- Bellman-Ford algorithm (16:33, 4 July 2022)
- Δ-stepping, C++, MPI, Parallel Boost Graph Library (10:06, 5 July 2022)
- Δ-stepping, Gap (10:19, 5 July 2022)
- Δ-stepping algorithm (10:23, 5 July 2022)
- Johnson's, C++, Boost Graph Library (10:29, 5 July 2022)
- Floyd-Warshall, C++, Boost Graph Library (10:38, 5 July 2022)
- Floyd-Warshall, Python, NetworkX (10:42, 5 July 2022)
- Floyd-Warshall, Java, JGraphT (10:45, 5 July 2022)
- Floyd-Warshall algorithm (10:52, 5 July 2022)
- Floyd-Warshall, scalability (10:53, 5 July 2022)
- Purdom's algorithm (13:00, 5 July 2022)
- Boruvka's, C++, MPI, Parallel Boost Graph Library (13:15, 5 July 2022)
- Boruvka's, RCC for CPU (13:19, 5 July 2022)
- Boruvka's, RCC for GPU (13:24, 5 July 2022)
- Boruvka's, scalability (13:37, 5 July 2022)
- Boruvka's, locality (13:49, 5 July 2022)
- Boruvka's algorithm (13:54, 5 July 2022)
- BFS, RCC for CPU (14:01, 5 July 2022)
- BFS, RCC for GPU (14:02, 5 July 2022)
- Kruskal's, C++, Boost Graph Library (09:47, 6 July 2022)
- Kruskal's, C++, MPI, Parallel Boost Graph Library (09:54, 6 July 2022)
- Kruskal's, Python, NetworkX (09:58, 6 July 2022)
- Kruskal's, Java, JGraphT (10:02, 6 July 2022)
- Prim's, C++, Boost Graph Library (10:08, 6 July 2022)
- Prim's, Java, JGraphT (10:12, 6 July 2022)
- Ullman's, C++, Chemical Descriptors Library (12:09, 6 July 2022)
- Ullman's, C++, VF Library (12:12, 6 July 2022)
- VF2, C++, VF Library (12:20, 6 July 2022)
- VF2, C++, Boost Graph Library (12:23, 6 July 2022)
- VF2, Python, NetworkX (12:26, 6 July 2022)
- Disjoint set union, Boost Graph Library (14:16, 6 July 2022)
- Disjoint set union, Java, JGraphT (14:20, 6 July 2022)
- Tarjan's strongly connected components, C++, Boost Graph Library (14:28, 6 July 2022)
- Tarjan's strongly connected components, Java, WebGraph (14:32, 6 July 2022)
- Tarjan's strongly connected components, Java, JGraphT (14:35, 6 July 2022)
- Tarjan's strongly connected components, Python, NetworkX (14:41, 6 July 2022)
- Tarjan's strongly connected components, Python/C++, NetworKit (14:45, 6 July 2022)
- Purdom's, Boost Graph Library (15:06, 6 July 2022)
- DCSC algorithm for finding the strongly connected components (15:11, 6 July 2022)
- DCSC for finding the strongly connected components, C++, MPI, Parallel Boost Graph Library (15:21, 6 July 2022)
- Tarjan's biconnected components, C++, Boost Graph Library (15:29, 6 July 2022)
- Tarjan's biconnected components, Python, NetworkX (15:32, 6 July 2022)
- Tarjan's biconnected components, Java, JGraphT (15:36, 6 July 2022)
- Tarjan-Vishkin biconnected components algorithm (15:47, 6 July 2022)
- Tarjan-Vishkin biconnected components, scalability (15:48, 6 July 2022)
- Ford–Fulkerson, C++, Boost Graph Library (09:19, 7 July 2022)
- Ford–Fulkerson, Python, NetworkX (09:23, 7 July 2022)
- Ford–Fulkerson, Java, JGraphT (09:30, 7 July 2022)
- Preflow-Push, C++, Boost Graph Library (09:38, 7 July 2022)
- Preflow-Push, Python, NetworkX (09:41, 7 July 2022)
- Hungarian, Java, JGraphT (09:47, 7 July 2022)
- Hopcroft–Karp, Java, JGraphT (09:54, 7 July 2022)
- Longest shortest path, Java, WebGraph (10:01, 7 July 2022)
- Longest shortest path, Python/C++, NetworKit (10:04, 7 July 2022)
- DFS, C++, Boost Graph Library (10:11, 7 July 2022)
- DFS, C++, MPI, Parallel Boost Graph Library (10:14, 7 July 2022)
- DFS, Python, NetworkX (10:17, 7 July 2022)
- Breadth-first search (BFS) (10:20, 7 July 2022)
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form (12:09, 7 July 2022)
- Cholesky decomposition, locality (12:46, 7 July 2022)
- Cholesky decomposition, SCALAPACK (12:51, 7 July 2022)
- Cholesky decomposition, scalability (12:53, 7 July 2022)
- Cooley-Tukey, locality (13:50, 7 July 2022)
- Lanczos, MPI, OpenMP (16:47, 7 July 2022)
- Lanczos, C++, MPI (17:03, 7 July 2022)
- Lanczos, C++, MPI, 2 (17:57, 7 July 2022)
- Lanczos, C, MPI (18:02, 7 July 2022)
- Lanczos, C++, MPI, 3 (18:07, 7 July 2022)
- One step of the dqds, LAPACK (09:46, 8 July 2022)
- One step of the dqds algorithm (09:51, 8 July 2022)
- Horners, locality (10:11, 8 July 2022)
- Horners method (10:15, 8 July 2022)
- Dense matrix-vector multiplication, locality (10:24, 8 July 2022)
- Dense matrix-vector multiplication, scalability (10:30, 8 July 2022)
- Dense matrix multiplication, locality (10:44, 8 July 2022)
- Dense matrix multiplication, scalability (10:50, 8 July 2022)
- Dense matrix multiplication (serial version for real matrices) (10:55, 8 July 2022)
- Pairwise summation of numbers, locality (12:46, 8 July 2022)
- Pairwise summation of numbers, scalability (12:50, 8 July 2022)
- Pairwise summation of numbers (12:52, 8 July 2022)
- Dense matrix-vector multiplication (12:54, 8 July 2022)
- Uniform norm of a vector, locality (14:29, 8 July 2022)
- Dot product, locality (14:38, 8 July 2022)
- Dot product, scalability (14:45, 8 July 2022)
- Dot product (14:49, 8 July 2022)
- The serial-parallel summation method, locality (14:59, 8 July 2022)
- The serial-parallel summation method, scalability (15:08, 8 July 2022)
- The serial-parallel summation method (15:12, 8 July 2022)
- Gaussian elimination, compact scheme for tridiagonal matrices, serial version (15:45, 8 July 2022)
- Stone doubling algorithm for the LU decomposition of a tridiagonal matrix (15:51, 8 July 2022)
- LU decomposition via Gaussian elimination, locality (16:03, 8 July 2022)
- LU decomposition via Gaussian elimination, scalability (16:09, 8 July 2022)
- LU decomposition via Gaussian elimination (16:13, 8 July 2022)
- Givens method, locality (16:27, 8 July 2022)
- Givens method (16:32, 8 July 2022)
- Householder (reflections) method for the QR decomposition, locality (08:20, 9 July 2022)
- Householder (reflections) method for the QR decomposition, SCALAPACK (08:33, 9 July 2022)
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, locality (08:41, 9 July 2022)
- Householder (reflections) method for reducing a symmetric matrix to tridiagonal form, SCALAPACK (08:44, 9 July 2022)
- Householder (reflections) method for the QR decomposition of a (real) Hessenberg matrix (08:51, 9 July 2022)
- Givens (rotations) method for the QR decomposition of a (real) Hessenberg matrix (08:52, 9 July 2022)
- Householder (reflections) reduction of a matrix to bidiagonal form, locality (11:05, 12 July 2022)
- Householder (reflections) reduction of a matrix to bidiagonal form, SCALAPACK (11:09, 12 July 2022)
- HPCG, locality (11:27, 12 July 2022)
- HPCG, scalability (11:31, 12 July 2022)
- BiCGStab, MIT (11:41, 12 July 2022)
- BiCGStab, HYPRE (11:49, 12 July 2022)
- BiCGStab, NVIDIA AmgX (11:52, 12 July 2022)
- Kaczmarz's, MATLAB1 (15:29, 12 July 2022)
- Kaczmarz's, MATLAB2 (15:32, 12 July 2022)
- Kaczmarz's, MATLAB3 (15:37, 12 July 2022)
- Linpack, locality (16:06, 12 July 2022)
- Linpack, HPL (16:11, 12 July 2022)
- Linpack benchmark (16:15, 12 July 2022)
- Thomas algorithm, locality (09:15, 14 July 2022)
- Thomas algorithm, pointwise version (09:20, 14 July 2022)
- Thomas, locality (09:29, 14 July 2022)
- Repeated Thomas, locality (11:02, 14 July 2022)
- Two-sided Thomas, locality (11:50, 14 July 2022)
- Two-sided Thomas algorithm, pointwise version (11:57, 14 July 2022)
- Repeated two-sided Thomas, locality (13:22, 14 July 2022)
- Complete cyclic reduction, locality (13:49, 14 July 2022)
- Complete cyclic reduction, scalability (13:55, 14 July 2022)
- Forward substitution (09:48, 18 July 2022)
- Backward substitution, locality (10:01, 18 July 2022)
- Backward substitution, scalability (14:27, 18 July 2022)
- Backward substitution (14:31, 18 July 2022)
- Binary search, locality (16:23, 18 July 2022)
- Binary search, С (16:27, 18 July 2022)
- Binary search, C++ (16:30, 18 July 2022)
- Binary search, Java (16:33, 18 July 2022)
- Binary search, .NET Framework 2.0 (16:36, 18 July 2022)
- Binary search, Python (16:39, 18 July 2022)
- Single-qubit transform of a state vector, locality (15:38, 19 July 2022)
- Single-qubit transform of a state vector, scalability (15:48, 19 July 2022)
- Single-qubit transform of a state vector (15:56, 19 July 2022)
- K-means clustering, scalability1 (16:09, 19 July 2022)
- K-means clustering, scalability2 (16:15, 19 July 2022)
- K-means clustering, scalability3 (16:21, 19 July 2022)
- K-means clustering, scalability4 (16:28, 19 July 2022)
- K-means clustering, CrimeStat (16:33, 19 July 2022)
- K-means clustering, Julia (16:35, 19 July 2022)
- K-means clustering, Apache Mahout (16:38, 19 July 2022)
- K-means clustering, Octave (16:40, 19 July 2022)
- K-means clustering, Spark (16:43, 19 July 2022)
- K-means clustering, Torch (16:51, 19 July 2022)
- K-means clustering, Weka (16:54, 19 July 2022)
- K-means clustering, Accord.NET (16:57, 19 July 2022)
- K-means clustering, OpenCV (17:04, 19 July 2022)
- K-means clustering, MLPACK (17:07, 19 July 2022)
- K-means clustering, SciPy (17:09, 19 July 2022)
- K-means clustering, scikit-learn (17:12, 19 July 2022)
- K-means clustering, R (17:14, 19 July 2022)
- K-means clustering, ELKI (17:16, 19 July 2022)
- K-means clustering, Ayasdi (17:19, 19 July 2022)
- K-means clustering, Stata (17:24, 19 July 2022)
- K-means clustering, Mathematica (17:27, 19 July 2022)
- K-means clustering, MATLAB (17:30, 19 July 2022)
- K-means clustering, SAS (17:33, 19 July 2022)
- K-means clustering, RapidMiner (17:37, 19 July 2022)
- K-means clustering, SAP HANA (17:40, 19 July 2022)
- Face recognition, scalability (16:26, 20 July 2022)
- SDDP, scalability (16:36, 20 July 2022)
- Newton's method for systems of nonlinear equations, scalability1 (16:53, 20 July 2022)
- Newton's method for systems of nonlinear equations, scalability2 (16:57, 20 July 2022)
- Newton's method for systems of nonlinear equations, scalability3 (17:03, 20 July 2022)
- Newton's method for systems of nonlinear equations, scalability4 (17:13, 20 July 2022)
- Newton's method for systems of nonlinear equations, ALIAS C++ (17:17, 20 July 2022)
- Newton's method for systems of nonlinear equations, Numerical Recipes (17:20, 20 July 2022)
- Newton's method for systems of nonlinear equations, Sundials (17:22, 20 July 2022)
- Newton's method for systems of nonlinear equations, Numerical Mathematics - NewtonLib (17:24, 20 July 2022)
- Newton's method for systems of nonlinear equations, PETSc (17:26, 20 July 2022)
- Newton's method for systems of nonlinear equations, parallel1 (11:40, 21 July 2022)
- Newton's method for systems of nonlinear equations, parallel2 (11:42, 21 July 2022)
- Newton's method for systems of nonlinear equations, parallel3 (11:44, 21 July 2022)
- Numerical quadrature (cubature) rules on an interval (for a multidimensional cube), scalability (12:09, 21 July 2022)
- Poisson equation, solving with DFT, locality (12:32, 21 July 2022)
- Poisson equation, solving with DFT, scalability (12:41, 21 July 2022)
- Poisson equation, solving with DFT, FFTW (15:25, 21 July 2022)
- Poisson equation, solving with DFT, FFTE (15:30, 21 July 2022)
- Poisson equation, solving with DFT, P3DFFT (15:40, 21 July 2022)
- Poisson equation, solving with DFT, cuFFT (15:43, 21 July 2022)
- Poisson equation, solving with DFT, AccFFT (15:47, 21 July 2022)
- Poisson equation, solving with DFT, MKL FFT (15:50, 21 July 2022)
- Poisson equation, solving with DFT, PFFT (15:53, 21 July 2022)
- Poisson equation, solving with DFT (15:58, 21 July 2022)
- Meet-in-the-middle attack, scalability (16:15, 21 July 2022)
- Meet-in-the-middle attack, implementation1 (16:18, 21 July 2022)
- Meet-in-the-middle attack, implementation2 (16:20, 21 July 2022)
- Meet-in-the-middle attack, implementation3 (16:23, 21 July 2022)
- BFS, VGL (16:29, 25 November 2022)
- Dijkstra, VGL, push (09:36, 28 November 2022)
- Dijkstra, VGL, pull (09:40, 28 November 2022)
- HITS, VGL (15:15, 28 November 2022)
- PageRank, VGL (15:22, 28 November 2022)
- Cholesky decomposition (18:37, 2 July 2023)