Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators
暂无分享,去创建一个
Ronald R. Coifman | Boaz Nadler | Ioannis G. Kevrekidis | Stéphane Lafon | B. Nadler | R. Coifman | I. Kevrekidis | S. Lafon
[1] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[2] B. Matkowsky,et al. Eigenvalues of the Fokker–Planck Operator and the Approach to Equilibrium for Diffusions in Potential Fields , 1981 .
[3] C. Gardiner. Handbook of Stochastic Methods , 1983 .
[4] H. Risken. Fokker-Planck Equation , 1984 .
[5] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[6] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[7] C. Schütte,et al. From Simulation Data to Conformational Ensembles , 1999 .
[8] Wilhelm Huisinga,et al. From simulation data to conformational ensembles: Structure and dynamics‐based methods , 1999 .
[9] Yair Weiss,et al. Segmentation using eigenvectors: a unifying view , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[10] Naftali Tishby,et al. Data Clustering by Markovian Relaxation and the Information Bottleneck Method , 2000, NIPS.
[11] Jianbo Shi,et al. A Random Walks View of Spectral Segmentation , 2001, AISTATS.
[12] Mikhail Belkin,et al. Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering , 2001, NIPS.
[13] Michael I. Jordan,et al. On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.
[14] Zoubin Ghahramani,et al. Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions , 2003, ICML 2003.
[15] Bernhard Schölkopf,et al. Learning with Local and Global Consistency , 2003, NIPS.
[16] A. ADoefaa,et al. ? ? ? ? f ? ? ? ? ? , 2003 .
[17] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[18] Jianbo Shi,et al. Multiclass spectral clustering , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[19] Pietro Perona,et al. Self-Tuning Spectral Clustering , 2004, NIPS.
[20] M. Eckho. PRECISE ASYMPTOTICS OF SMALL EIGENVALUES OF REVERSIBLE DIFFUSIONS IN THE METASTABLE REGIME , 2004 .
[21] Ulrike von Luxburg,et al. On the Convergence of Spectral Clustering on Random Samples: The Normalized Case , 2004, COLT.
[22] Ioannis G. Kevrekidis,et al. Equation-free: The computer-aided analysis of complex multiscale systems , 2004 .
[23] François Fouss,et al. The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering , 2004, ECML.
[24] Nicolas Le Roux,et al. Learning Eigenfunctions Links Spectral Embedding and Kernel PCA , 2004, Neural Computation.
[25] Ann B. Lee,et al. Geometric diffusions as a tool for harmonic analysis and structure definition of data: diffusion maps. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[26] Clustering Using a Random Walk Based Distance Measure , 2005, ESANN.
[27] Ulrike von Luxburg,et al. From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians , 2005, COLT.
[28] B. Nadler,et al. Diffusion maps, spectral clustering and reaction coordinates of dynamical systems , 2005, math/0503445.
[29] Ann B. Lee,et al. Diffusion maps and coarse-graining: a unified framework for dimensionality reduction, graph partitioning, and data set parameterization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.