A New Scaling and Squaring Algorithm for the Matrix Exponential
By Awad H. Al-Mohy, Nicholas John Higham. SIAM Journal on Matrix Analysis and Applications, 2009
387 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/7de1d1e1fa7516acdba214916f138885d54159f3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- David Martínez-Rubio
- Eric P. Xing
- Pradeep Ravikumar
- Maximilian Nickel
- Aditya Grover
- Bryon Aragam
- Xun Zheng
- Yaron Lipman
In Computational Theory and Mathematics
- David Martínez-Rubio
- Eric P. Xing
- Pradeep Ravikumar
- Maximilian Nickel
- Aditya Grover
- Bryon Aragam
- Xun Zheng
- Yaron Lipman
Citations in the corpus
- Moser Flow: Divergence-based Generative Modeling on Manifolds (2021, background): “On the hyperboloid, on the other hand, the exponential map is numerically not well-behaved far away from the origin (Dooley and Wildberger, 1993; Al-Mohy and Higham, 2010).”
- DAGs with NO TEARS: Continuous Optimization for Structure Learning (2018, background): “A key conclusion from Theorem 1 is that h and its gradient only involve evaluating the matrix exponential, which is a well-studied function in numerical analysis, and whose O ( d 3 ) algorithm (Al-Mohy and Higham, 2009) is readily available in many scientific computing libraries.”
- Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group (2019, methodology): “We have that The differential of the exponential of matrices (d exp) A can be approximated to machine-precision computing the exponential of a 2 n × 2 n matrix, as described in (Al-Mohy & Higham, 2009a).”