ProbabilisticLinearSolver¶
- class probnum.linalg.solvers.ProbabilisticLinearSolver¶
Bases:
object
Compose a custom probabilistic linear solver.
Class implementing probabilistic linear solvers. Such (iterative) solvers infer solutions to problems of the form
\[Ax=b,\]where \(A \in \mathbb{R}^{n \times n}\) and \(b \in \mathbb{R}^{n}\). They return a probability measure which quantifies uncertainty in the output arising from finite computational resources or stochastic input. This class unifies and generalizes probabilistic linear solvers as described in the literature. 1 2 3 4
References
- 1
Hennig, P., Probabilistic Interpretation of Linear Solvers, SIAM Journal on Optimization, 2015, 25, 234-260
- 2
Cockayne, J. et al., A Bayesian Conjugate Gradient Method, Bayesian Analysis, 2019, 14, 937-1012
- 3
Bartels, S. et al., Probabilistic Linear Solvers: A Unifying View, Statistics and Computing, 2019
- 4
Wenger, J. and Hennig, P., Probabilistic Linear Solvers for Machine Learning, Advances in Neural Information Processing Systems (NeurIPS), 2020
See also
problinsolve
Solve linear systems in a Bayesian framework.
bayescg
Solve linear systems with prior information on the solution.
Examples