Characteristic classes | Differential topology
In mathematics, the Pontryagin classes, named after Lev Pontryagin, are certain characteristic classes of real vector bundles. The Pontryagin classes lie in cohomology groups with degrees a multiple of four. (Wikipedia).
Marc Levine: Refined enumerative geometry (Lecture 4)
The lecture was held within the framework of the Hausdorff Trimester Program: K-Theory and Related Fields. Lecture 4: Characteristic classes in Witt-cohomology Classical enumerative geometry relies heavily on the theory of Chern classes of vector bundles and the splitting principle, which
From playlist HIM Lectures: Trimester Program "K-Theory and Related Fields"
Loop products, closed geodesics and self-intersections - Nancy Hingston
Workshop on Geometric Functionals: Analysis and Applications Topic: Loop products, closed geodesics and self-intersections Speaker: Nancy Hingston Affiliation: The College of New Jersey Date: March 6, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
Lecture 8 | MIT 6.832 Underactuated Robotics, Spring 2009
Lecture 8: Dynamic programming (DP) and policy search Instructor: Russell Tedrake See the complete course at: http://ocw.mit.edu/6-832s09 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.832 Underactuated Robotics, Spring 2009
Duality for Rabinowitz-Floer homology - Alex Oancea
IAS/PU-Montreal-Paris-Tel-Aviv Symplectic Geometry Topic: Duality for Rabinowitz-Floer homology Speaker: Alex Oancea Affiliation: Institut de Mathématiques de Jussieu-Paris Rive Gauche Date: May 27, 2020 For more video please visit http://video.ias.edu
From playlist PU/IAS Symplectic Geometry Seminar
Michael Hopkins: Bernoulli numbers, homotopy groups, and Milnor
Abstract: In his address at the 1958 International Congress of Mathematicians Milnor described his joint work with Kervaire, relating Bernoulli numbers, homotopy groups, and the theory of manifolds. These ideas soon led them to one of the most remarkable formulas in mathematics, relating f
From playlist Abel Lectures
Marc Levine: Refined enumerative geometry (Lecture 1)
The lecture was held within the framework of the Hausdorff Trimester Program: K-Theory and Related Fields. Marc Levine: Refined enumerative geometry Abstract: Lecture 1: Milnor-Witt sheaves, motivic homotopy theory and Chow-Witt groups We review the Hoplins-Morel construction of the Miln
From playlist HIM Lectures: Trimester Program "K-Theory and Related Fields"
Lecture 4 | MIT 6.832 Underactuated Robotics, Spring 2009
Lecture 4: Optimal control of the double integrator (continued) Instructor: Russell Tedrake See the complete course at: http://ocw.mit.edu/6-832s09 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.832 Underactuated Robotics, Spring 2009
Markus Banagl : The L-Homology fundamental class for singular spaces and the stratified Novikov
Abstract : An oriented manifold possesses an L-homology fundamental class which is an integral refinement of its Hirzebruch L-class and assembles to the symmetric signature. In joint work with Gerd Laures and James McClure, we give a construction of such an L-homology fundamental class for
From playlist Topology
This lecture was held by Abel Laureate John Milnor at The University of Oslo, May 25, 2011 and was part of the Abel Prize Lectures in connection with the Abel Prize Week celebrations. Program for the Abel Lectures 2011 1. "Spheres" by Abel Laureate John Milnor, Institute for Mathematical
From playlist Abel Lectures
Learning Optimal Control with Stochastic Models of Hamiltonian Dynamics for Shape & Function Optim.
Speaker: Chandrajit Bajaj (7/25/22) Abstract: Shape and Function Optimization can be achieved through Optimal Control over infinite-dimensional search space. All optimal control problems can be solved by first applying the Pontryagin maximum principle, and then computing a solution to the
From playlist Applied Geometry for Data Sciences 2022