Learning the geometry of common latent variables using alternating-diffusion

By Roy R. Lederman, Ronen Talmon. 2015

113 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Modeling and Simulation, Statistical and Nonlinear Physics

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. Francesco Locatello
2. Bernhard Schölkopf
3. Luigi Gresele
4. Paul K. Rubenstein
5. Arash Mehrjou
6. Stefan Bauer
7. Dominik Janzing
8. Arthur Gretton

In Modeling and Simulation

1. Bernhard Schölkopf

In Statistical and Nonlinear Physics

1. Bernhard Schölkopf
2. Francesco Locatello
3. Manuel Gomez-Rodriguez
4. Jure Leskovec

Citations in the corpus

• The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA (2019, background): “Bearing a strong resemblance to our considered setting, [27] proposes a sequence of diffusion maps to find the common source of variability captured by multiple sensors, discarding irrelevant sensor-specific effects.”