Linked from

The 38 pages that link to Linear algebra, each with the reason it gives.

• Finite element methodNarrower topic: After discretization, many finite element problems reduce to solving a system of linear equations.

• Computer graphicsRelated: Matrices express the rotations, scaling, and projections used to position visual objects.

• Quantum computingRelated: Quantum states are represented by vectors, while gates act as matrices.

• Field (mathematics)Related: Vector spaces and matrices commonly use field elements as scalars and entries.

• Homogeneous coordinatesRelated: Matrix multiplication supplies the basic operations on homogeneous coordinate tuples.

• AlgebraBroader topic: It extends equation-solving to many variables and transformations.

• Analytic geometryRelated: It extends coordinate geometry to higher dimensions and systematic transformations.

• Kalman filterNarrower topic: State transitions and measurement relationships are represented with matrix operations.

• Abstract algebraCompared with: It specializes in vector spaces and linear transformations rather than algebraic structures broadly.

• Mathematical physicsRelated: Quantum states, symmetries, and many physical transformations use vector spaces and linear operators.

• Discrete Fourier transformNarrower topic: The DFT is a linear map from a finite sample vector to a coefficient vector.

• Commutative algebraNarrower topic: Commutative algebra generalizes scalar methods from fields to arbitrary commutative rings.

• Deep learningNarrower topic: Neural-network layers rely on matrix operations to transform batches of data.

• FieldNarrower topic: Its standard theory is formulated over fields.

• Mathematical economicsRelated: Matrices compactly represent systems of markets, technologies, and strategic interactions.

• IncidenceNarrower topic: Incidence matrices let linear-algebraic tools expose structural constraints.

• Square matrixNarrower topic: Square matrices are central representations of linear maps between finite-dimensional spaces.

• Applied mathematicsBroader topic: Vectors and matrices encode data, transformations, and coupled unknowns in applied problems.

• Convolutional neural networkRelated: Convolutions and learned transformations are implemented through tensor operations.

• Cayley–Hamilton theoremNarrower topic: The theorem is a basic structural result about finite-dimensional linear maps.

• Convex analysisNarrower topic: Convex analysis relies on its vector and dual-space framework but asks geometric nonlinear questions.

• Inverse elementRelated: Invertible matrices reverse linear transformations and solve square linear systems.

• Petri netNarrower topic: Matrix methods expose invariants and transition effects in Petri nets.

• History of algebraNarrower topic: Its modern form grew from equation-solving, geometry, and the study of transformations.

• Cramer's ruleNarrower topic: Cramer's rule is one classical result within the broader study of linear systems.

• Data scienceRelated: Many data representations and machine-learning algorithms use vectors and matrices.

• Mathematical structureRelated: Vector spaces are structured sets whose operations support broad transferable theorems.

• 3D computer graphicsRelated: Transforms use vectors and matrices to position, rotate, and scale objects.

• Vector processorRelated: Matrix and vector computations are common targets for vector hardware.

• Magic squareNarrower topic: Magic-square conditions form a system of linear equations on the cell entries.

• Wassily LeontiefRelated: Matrix methods make Leontief’s system of interindustry equations solvable.

• Computational scienceRelated: Large matrix operations underpin simulations, data analysis, and numerical solvers.

• John Vincent AtanasoffRelated: Solving large systems of linear equations motivated Atanasoff’s search for a faster calculating machine.

• Perron–Frobenius theoremNarrower topic: The theorem builds on eigenvalues and eigenvectors, core objects of linear algebra.

• GeomathematicsNarrower topic: It underlies the large systems of equations used to fit and invert geoscience data.

• Liouville's formulaNarrower topic: The trace and determinant identities underlying the result come from linear algebra.

• Mathematical methods in physicsBroader topic: It organizes coupled equations, coordinate changes, and quantum states.

• Rouché–Capelli theoremNarrower topic: The theorem belongs to the classical theory of solving linear equations.