Publisher
Springer Berlin Heidelberg
Reference12 articles.
1. Saul, L., Roweis, S.: Think globally, fit locally: unsupervised learning of low dimensional manifolds. The Journal of Machine Learning Research 4, 119–155 (2003)
2. Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation 15(6), 1373–1396 (2003)
3. Tenenbaum, J.B., de Silva, V., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319–2323 (2000)
4. Gerber, S., Tasdizen, T., Fletcher, P.T., Joshi, S., Whitaker, R.: Manifold modeling for brain population analysis. Medical Image Analysis 14(5), 643–653 (2010)
5. Etyngier, P., Ségonne, F., Keriven, R.: Shape priors using manifold learning techniques. In: 11th International Conference on Computer Vision, pp. 1–8. IEEE (2007)
Cited by
182 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献