Gotowa bibliografia na temat „Riemannian and barycentric geometry”
Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych
Spis treści
Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „Riemannian and barycentric geometry”.
Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.
Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.
Artykuły w czasopismach na temat "Riemannian and barycentric geometry"
Pihajoki, Pauli, Matias Mannerkoski i Peter H. Johansson. "Barycentric interpolation on Riemannian and semi-Riemannian spaces". Monthly Notices of the Royal Astronomical Society 489, nr 3 (2.09.2019): 4161–69. http://dx.doi.org/10.1093/mnras/stz2447.
Pełny tekst źródłaMiranda Jr., Gastão F., Gilson Giraldi, Carlos E. Thomaz i Daniel Millàn. "Composition of Local Normal Coordinates and Polyhedral Geometry in Riemannian Manifold Learning". International Journal of Natural Computing Research 5, nr 2 (kwiecień 2015): 37–68. http://dx.doi.org/10.4018/ijncr.2015040103.
Pełny tekst źródłaSabatini, Luca. "Volume Comparison in the presence of a Gromov-Hausdorff ε−approximation II". Annals of West University of Timisoara - Mathematics and Computer Science 56, nr 1 (1.07.2018): 99–135. http://dx.doi.org/10.2478/awutm-2018-0008.
Pełny tekst źródłaWu, H., i Wilhelm Klingenberg. "Riemannian Geometry." American Mathematical Monthly 92, nr 7 (sierpień 1985): 519. http://dx.doi.org/10.2307/2322529.
Pełny tekst źródłaLord, Nick, M. P. do Carmo, S. Gallot, D. Hulin, J. Lafontaine, I. Chavel i D. Martin. "Riemannian Geometry". Mathematical Gazette 79, nr 486 (listopad 1995): 623. http://dx.doi.org/10.2307/3618122.
Pełny tekst źródłaMrugała, R. "Riemannian geometry". Reports on Mathematical Physics 27, nr 2 (kwiecień 1989): 283–85. http://dx.doi.org/10.1016/0034-4877(89)90011-6.
Pełny tekst źródłaM.Osman, Mohamed. "Differentiable Riemannian Geometry". International Journal of Mathematics Trends and Technology 29, nr 1 (25.01.2016): 45–55. http://dx.doi.org/10.14445/22315373/ijmtt-v29p508.
Pełny tekst źródłaDimakis, Aristophanes, i Folkert Müller-Hoissen. "Discrete Riemannian geometry". Journal of Mathematical Physics 40, nr 3 (marzec 1999): 1518–48. http://dx.doi.org/10.1063/1.532819.
Pełny tekst źródłaBeggs, Edwin J., i Shahn Majid. "Poisson–Riemannian geometry". Journal of Geometry and Physics 114 (kwiecień 2017): 450–91. http://dx.doi.org/10.1016/j.geomphys.2016.12.012.
Pełny tekst źródłaStrichartz, Robert S. "Sub-Riemannian geometry". Journal of Differential Geometry 24, nr 2 (1986): 221–63. http://dx.doi.org/10.4310/jdg/1214440436.
Pełny tekst źródłaRozprawy doktorskie na temat "Riemannian and barycentric geometry"
Farina, Sofia. "Barycentric Subspace Analysis on the Sphere and Image Manifolds". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15797/.
Pełny tekst źródłaLord, Steven. "Riemannian non-commutative geometry /". Title page, abstract and table of contents only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phl8661.pdf.
Pełny tekst źródłaMaignant, Elodie. "Plongements barycentriques pour l'apprentissage géométrique de variétés : application aux formes et graphes". Electronic Thesis or Diss., Université Côte d'Azur, 2023. http://www.theses.fr/2023COAZ4096.
Pełny tekst źródłaAn MRI image has over 60,000 pixels. The largest known human protein consists of around 30,000 amino acids. We call such data high-dimensional. In practice, most high-dimensional data is high-dimensional only artificially. For example, of all the images that could be randomly generated by coloring 256 x 256 pixels, only a very small subset would resemble an MRI image of a human brain. This is known as the intrinsic dimension of such data. Therefore, learning high-dimensional data is often synonymous with dimensionality reduction. There are numerous methods for reducing the dimension of a dataset, the most recent of which can be classified according to two approaches.A first approach known as manifold learning or non-linear dimensionality reduction is based on the observation that some of the physical laws behind the data we observe are non-linear. In this case, trying to explain the intrinsic dimension of a dataset with a linear model is sometimes unrealistic. Instead, manifold learning methods assume a locally linear model.Moreover, with the emergence of statistical shape analysis, there has been a growing awareness that many types of data are naturally invariant to certain symmetries (rotations, reparametrizations, permutations...). Such properties are directly mirrored in the intrinsic dimension of such data. These invariances cannot be faithfully transcribed by Euclidean geometry. There is therefore a growing interest in modeling such data using finer structures such as Riemannian manifolds. A second recent approach to dimension reduction consists then in generalizing existing methods to non-Euclidean data. This is known as geometric learning.In order to combine both geometric learning and manifold learning, we investigated the method called locally linear embedding, which has the specificity of being based on the notion of barycenter, a notion a priori defined in Euclidean spaces but which generalizes to Riemannian manifolds. In fact, the method called barycentric subspace analysis, which is one of those generalizing principal component analysis to Riemannian manifolds, is based on this notion as well. Here we rephrase both methods under the new notion of barycentric embeddings. Essentially, barycentric embeddings inherit the structure of most linear and non-linear dimension reduction methods, but rely on a (locally) barycentric -- affine -- model rather than a linear one.The core of our work lies in the analysis of these methods, both on a theoretical and practical level. In particular, we address the application of barycentric embeddings to two important examples in geometric learning: shapes and graphs. In addition to practical implementation issues, each of these examples raises its own theoretical questions, mostly related to the geometry of quotient spaces. In particular, we highlight that compared to standard dimension reduction methods in graph analysis, barycentric embeddings stand out for their better interpretability. In parallel with these examples, we characterize the geometry of locally barycentric embeddings, which generalize the projection computed by locally linear embedding. Finally, algorithms for geometric manifold learning, novel in their approach, complete this work
Lidberg, Petter. "Barycentric and harmonic coordinates". Thesis, Uppsala universitet, Algebra och geometri, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-179487.
Pełny tekst źródłaHall, Stuart James. "Numerical methods and Riemannian geometry". Thesis, Imperial College London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538692.
Pełny tekst źródłaFerreira, Ana Cristina Castro. "Riemannian geometry with skew torsion". Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526550.
Pełny tekst źródłaWu, Bao Qiang. "Geometry of complete Riemannian Submanifolds". Lyon 1, 1998. http://www.theses.fr/1998LYO10064.
Pełny tekst źródłaBoarotto, Francesco. "Topics in sub-Riemannian geometry". Doctoral thesis, SISSA, 2016. http://hdl.handle.net/20.500.11767/4881.
Pełny tekst źródłaPalmer, Ian Christian. "Riemannian geometry of compact metric spaces". Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34744.
Pełny tekst źródłaRaineri, Emanuele. "Quantum Riemannian geometry of finite sets". Thesis, Queen Mary, University of London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414738.
Pełny tekst źródłaKsiążki na temat "Riemannian and barycentric geometry"
Gallot, Sylvestre, Dominique Hulin i Jacques Lafontaine. Riemannian Geometry. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-97242-3.
Pełny tekst źródłaPetersen, Peter. Riemannian Geometry. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-6434-5.
Pełny tekst źródłaCarmo, Manfredo Perdigão do. Riemannian Geometry. Boston, MA: Birkhäuser Boston, 1992. http://dx.doi.org/10.1007/978-1-4757-2201-7.
Pełny tekst źródłaGallot, Sylvestre, Dominique Hulin i Jacques Lafontaine. Riemannian Geometry. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18855-8.
Pełny tekst źródłaPetersen, Peter. Riemannian Geometry. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26654-1.
Pełny tekst źródłaGallot, Sylvestre, Dominique Hulin i Jacques Lafontaine. Riemannian Geometry. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-97026-9.
Pełny tekst źródła1959-, Hulin D., i Lafontaine, J. 1944 Mar. 10-, red. Riemannian geometry. Berlin: Springer-Verlag, 1987.
Znajdź pełny tekst źródłaSakai, T. Riemannian geometry. Providence, R.I: American Mathematical Society, 1996.
Znajdź pełny tekst źródłaRiemannian geometry. Wyd. 2. Berlin: W. de Gruyter, 1995.
Znajdź pełny tekst źródłaCarmo, Manfredo Perdigão do. Riemannian geometry. Boston: Birkhäuser, 1992.
Znajdź pełny tekst źródłaCzęści książek na temat "Riemannian and barycentric geometry"
Bambi, Cosimo. "Riemannian Geometry". W Introduction to General Relativity, 85–105. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1090-4_5.
Pełny tekst źródłaConlon, Lawrence. "Riemannian Geometry". W Differentiable Manifolds, 293–348. Boston, MA: Birkhäuser Boston, 1993. http://dx.doi.org/10.1007/978-1-4757-2284-0_10.
Pełny tekst źródłaAubin, Thierry. "Riemannian Geometry". W Some Nonlinear Problems in Riemannian Geometry, 1–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-13006-3_1.
Pełny tekst źródłaKumaresan, S. "Riemannian Geometry". W A Course in Differential Geometry and Lie Groups, 232–80. Gurgaon: Hindustan Book Agency, 2002. http://dx.doi.org/10.1007/978-93-86279-08-8_5.
Pełny tekst źródłaGadea, P. M., i J. Muñoz Masqué. "Riemannian Geometry". W Analysis and Algebra on Differentiable Manifolds, 233–349. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3564-6_6.
Pełny tekst źródłaKoch, Helmut. "Riemannian geometry". W Introduction to Classical Mathematics I, 182–209. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3218-3_14.
Pełny tekst źródłaMcInerney, Andrew. "Riemannian Geometry". W Undergraduate Texts in Mathematics, 195–270. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7732-7_5.
Pełny tekst źródłaChow, Bennett, Peng Lu i Lei Ni. "Riemannian geometry". W Hamilton’s Ricci Flow, 1–93. Providence, Rhode Island: American Mathematical Society, 2006. http://dx.doi.org/10.1090/gsm/077/01.
Pełny tekst źródłaGadea, Pedro M., Jaime Muñoz Masqué i Ihor V. Mykytyuk. "Riemannian Geometry". W Analysis and Algebra on Differentiable Manifolds, 343–546. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-5952-7_6.
Pełny tekst źródłaHassani, Sadri. "Riemannian Geometry". W Mathematical Physics, 1143–77. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01195-0_37.
Pełny tekst źródłaStreszczenia konferencji na temat "Riemannian and barycentric geometry"
Moran, William, Stephen D. Howard, Douglas Cochran i Sofia Suvorova. "Sensor management via riemannian geometry". W 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2012. http://dx.doi.org/10.1109/allerton.2012.6483240.
Pełny tekst źródłaHadwiger, Markus, Thomas Theußl i Peter Rautek. "Riemannian Geometry for Scientific Visualization". W SA '22: SIGGRAPH Asia 2022. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3550495.3558227.
Pełny tekst źródłaGMIRA, B., i L. VERSTRAELEN. "A CURVATURE INEQUALITY FOR RIEMANNIAN SUBMANIFOLDS IN A SEMI–RIEMANNIAN SPACE FORM". W Geometry and Topology of Submanifolds IX. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789812817976_0016.
Pełny tekst źródłaLenz, Reiner, Rika Mochizuki i Jinhui Chao. "Iwasawa Decomposition and Computational Riemannian Geometry". W 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.1086.
Pełny tekst źródłaBejancu, Aurel. "Sub-Riemannian geometry and nonholonomic mechanics". W ALEXANDRU MYLLER MATHEMATICAL SEMINAR CENTENNIAL CONFERENCE. AIP, 2011. http://dx.doi.org/10.1063/1.3546072.
Pełny tekst źródłaChen, Guohua. "Digital Riemannian Geometry and Its Application". W International Conference on Advances in Computer Science and Engineering. Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/cse.2013.63.
Pełny tekst źródłaBarachant, Alexandre, Stphane Bon, Marco Congedo i Christian Jutten. "Common Spatial Pattern revisited by Riemannian geometry". W 2010 IEEE 12th International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2010. http://dx.doi.org/10.1109/mmsp.2010.5662067.
Pełny tekst źródłaZeestraten, Martijn J. A., Ioannis Havoutis, Sylvain Calinon i Darwin G. Caldwell. "Learning task-space synergies using Riemannian geometry". W 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017. http://dx.doi.org/10.1109/iros.2017.8202140.
Pełny tekst źródłaShao, Hang, Abhishek Kumar i P. Thomas Fletcher. "The Riemannian Geometry of Deep Generative Models". W 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2018. http://dx.doi.org/10.1109/cvprw.2018.00071.
Pełny tekst źródłaGordina, Maria. "Riemannian geometry of Diff(S1)/S1 revisited". W Proceedings of a Satellite Conference of ICM 2006. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812791559_0002.
Pełny tekst źródła