Self‐modelling warping functions
By Daniel Gervini, Theo Gasser. 2004
135 citations recorded by the source corpus.
Subfields: Molecular Biology, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/01ac436e0a9fe713138b172f274481785a4d6d56
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Victor M. Panaretos
- David Kraus
- H. Muller
- John H. Maddocks
- Rong Tang
- Jane-ling Wang
- Jeng-Min Chiou
- Fang Yao
In Statistics and Probability
- Victor M. Panaretos
- H. Muller
- David Kraus
- John H. Maddocks
- Rong Tang
- Jane-ling Wang
- Jeng-Min Chiou
- Han Lin Shang
Citations in the corpus
- Pairwise curve synchronization for functional data (2008, methodology): “The number of basis functions p was suggested to be approximately 3 − 4 times the number of features for self-modelling registration (Gervini & Gasser, 2004), motivating the choices 4 and 12.”
- Second-Order Comparison of Gaussian Random Functions and the Geometry of DNA Minicircles (2010, methodology): “On the other hand, more flexible methods such as warping (e.g., Gervini and Gasser 2004; Tang and Müller 2008) are inappropriate since nonrigid alignment will alter the second-order properties that are of principal interest.”