Cubic Spline Interpolation

By B. Kvasov. 2000

539 citations recorded by the source corpus.

Subfields: Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/f3426d70bee3416e52850756a6927c59f3affc6d

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

1. Srihari Nelakuditi
2. Romit Roy Choudhury
3. Dina Katabi
4. Nirupam Roy
5. Wenyuan Xu
6. Sanorita Dey

Citations in the corpus

• AccelPrint: Imperfections of Accelerometers Make Smartphones Trackable (2014, methodology): “Hence, AccelPrint employs a cubic spline interpolation [44] to construct new data points such that {T (k), S(k)} are now equally-spaced.”
• Emotion recognition using wireless signals (2016, background): “Linear warping is realized through a cubic spline interpolation [42].”
• Text embedding models can be great data engineers (2025, unknown): “This process involves a series of operations, such as: Here, f imp denotes missing-value interpolation (e.g. cubic-spline [28] or Gaussian-process [43]), f norm represents normalization (min–max or z -score), and ϕ extracts M handcrafted features (often M ≫ TFK ; e.g. TSFEL yields M > 9000 [5]).”