Fast Multidimensional Entropy Estimation by $k$-d Partitioning

By Dan Stowell, Mark D. Plumbley. 2009

71 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Bernhard Schölkopf
2. Dominik Janzing
3. Jan Peters
4. Joris M. Mooij
5. David Lopez-Paz
6. Kun Zhang
7. Jakob Zscheischler
8. Peter Buhlmann

In Computer Vision and Pattern Recognition

1. Jan Peters
2. Dominik Janzing
3. Joris M. Mooij
4. Bernhard Schölkopf
5. Luc Van Gool
6. Arthur Gretton
7. Dacheng Tao
8. Ming-Hsuan Yang

Citations in the corpus

• Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks (2014, background): “, 1994) sp6 ITE: Shannon spacing VKDE (Noughabi and Noughabi, 2013) KDP ITE: Shannon KDP (Stowell and Plumbley, 2009) PSD ITE: Shannon PSD SzegoT (Ramirez et al.”
• Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks (2014, background): “The method 3NN is based on k-nearest neighbors with k = 3, all sp* methods use Vasicek’s spacing method with various corrections, KDP uses k-d partitioning, PSD uses the power spectral density representation and Szego’s theorem, ME1 and ME2 use the maximum entropy distribution method, and EdE uses t”