Diffusion Maps, Reduction Coordinates, and Low Dimensional Representation of Stochastic Systems

By Ronald R. Coifman, Ioannis G. Kevrekidis, Stéphane Lafon, Mauro Maggioni, Boaz Nadler. Multiscale Modeling & simulation, 2008

315 citations recorded by the source corpus.

Subfields: Condensed Matter Physics, Radiology, Nuclear Medicine and Imaging, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5288bcebfd6a6d65213c1c8cfefc2a8e98cc6e94

How researchers see this paper

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

In Condensed Matter Physics

1. J. Nathan Kutz
2. Krithika Manohar
3. Bingni W. Brunton
4. Steven L. Brunton

In Radiology, Nuclear Medicine and Imaging

1. J. Nathan Kutz
2. Steven L. Brunton

In Statistics and Probability

1. J. Nathan Kutz
2. Steven L. Brunton
3. Bingni W. Brunton
4. Krithika Manohar
5. Igor Mezi'c
6. Maizar Raissi
7. G. Em Karniadakis
8. Hassan Arbabi

Citations in the corpus

• Universal Local Parametrizations via Heat Kernels and Eigenfunctions of the Laplacian (2007, unknown): “, im = m [47, 2, 4, 10, 12, 9].”
• Local Kernels and the Geometric Structure of Data (2014, unknown): “This generalizes the views of [16, 8, 5, 7, 24, 28] which connected the diffusion maps construction to the generator of a Markov process in the case of a gradient flow.”
• Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns (2017, methodology): “[26] R.”