His primary areas of investigation include Algorithm, Polygon mesh, Topology, Linear system and Artificial intelligence. His study in the field of Computational geometry also crosses realms of Geometric similarity. He combines subjects such as Rigid transformation, Conformal map, Invariant and Geometric modeling with his study of Topology.
His Invariant research incorporates elements of Point cloud, Shape analysis and Convolutional neural network. His Linear system research integrates issues from Interpolation, Linear least squares, Least squares, Coefficient matrix and Mathematical optimization. In Artificial intelligence, Yaron Lipman works on issues like Computer vision, which are connected to Computer graphics and Animation.
His scientific interests lie mostly in Algorithm, Surface, Artificial intelligence, Conformal map and Mathematical analysis. His Algorithm research is multidisciplinary, incorporating elements of Mathematical optimization, Relaxation, Linear system and Euclidean geometry. His work deals with themes such as Rigid transformation, Coefficient matrix, Laplace operator and Interpolation, which intersect with Linear system.
His work carried out in the field of Surface brings together such families of science as Polygon mesh, State and Combinatorics. The Artificial intelligence study combines topics in areas such as Computer vision and Pattern recognition. He interconnects Numerical analysis and Geodesic, Distortion, Topology in the investigation of issues within Conformal map.
Yaron Lipman mainly focuses on Artificial neural network, Point cloud, Algorithm, Artificial intelligence and Level set. His study in Point cloud is interdisciplinary in nature, drawing from both Sign and Implicit function. Yaron Lipman works in the field of Algorithm, namely Regularization.
He has included themes like Surface, State and Pattern recognition in his Artificial intelligence study. His Surface study introduces a deeper knowledge of Geometry. His Equivariant map research includes elements of Discrete mathematics and Invariant.
His main research concerns Artificial neural network, Point cloud, Invariant, Symmetric group and Universality. His Artificial neural network research is multidisciplinary, incorporating perspectives in Training set, Implicit function, Raw data, Deep learning and Sign. His Point cloud study deals with the bigger picture of Artificial intelligence.
The concepts of his Artificial intelligence study are interwoven with issues in Sampling, Manifold, Function, Generalization and Sample. His research on Invariant concerns the broader Pure mathematics. His Level set research is multidisciplinary, relying on both Algorithm and Regularization.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Laplacian surface editing
O. Sorkine;D. Cohen-Or;Y. Lipman;M. Alexa.
symposium on geometry processing (2004)
Linear rotation-invariant coordinates for meshes
Yaron Lipman;Olga Sorkine;David Levin;Daniel Cohen-Or.
international conference on computer graphics and interactive techniques (2005)
Blended intrinsic maps
Vladimir G. Kim;Yaron Lipman;Thomas Funkhouser.
international conference on computer graphics and interactive techniques (2011)
Green Coordinates
Yaron Lipman;David Levin;Daniel Cohen-Or.
international conference on computer graphics and interactive techniques (2008)
Möbius voting for surface correspondence
Yaron Lipman;Thomas Funkhouser.
international conference on computer graphics and interactive techniques (2009)
Differential coordinates for interactive mesh editing
Y. Lipman;O. Sorkine;D. Cohen-Or;D. Levin.
Proceedings Shape Modeling Applications, 2004. (2004)
Coordinates for instant image cloning
Zeev Farbman;Gil Hoffer;Yaron Lipman;Daniel Cohen-Or.
international conference on computer graphics and interactive techniques (2009)
Parameterization-free projection for geometry reconstruction
Yaron Lipman;Daniel Cohen-Or;David Levin;Hillel Tal-Ezer.
international conference on computer graphics and interactive techniques (2007)
Differential Coordinates for Interactive Mesh Editing
Yaron Lipman;Olga Sorkine;Daniel Cohen-Or;David Levin.
Untitled Event (2004)
Biharmonic distance
Yaron Lipman;Raif M. Rustamov;Thomas A. Funkhouser.
ACM Transactions on Graphics (2010)
Profile was last updated on December 6th, 2021.
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