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Explore joint estimation and contour detection in large-scale image processing, focusing on textured image segmentation and image restoration using advanced optimization techniques.
Winning presentation by Nueva School on their solution for the MathWorks Math Modeling Challenge 2021, showcasing innovative approaches to technical computing and problem-solving.
Finalist team from Adlai E Stevenson High School presents their solution to the MathWorks Math Modeling Challenge 2021, showcasing innovative problem-solving skills in applied mathematics.
High school team presents innovative mathematical modeling solutions for the MathWorks Math Modeling Challenge, showcasing problem-solving skills and analytical thinking in a competitive environment.
Explore infinite-dimensional geometry with symmetry, focusing on algebraic models and their applications in statistics, tensor decomposition, and combinatorics.
Explore Hölder stability in quantitative photoacoustic tomography, focusing on reconstructing diffusion and absorption coefficients from partial internal data near boundaries.
Explore Ginzburg-Landau model of superconductivity, analyzing vortex patterns in 2D and 3D, energy minimizers, and vortex dynamics with expert Sylvia Serfaty from NYU's Courant Institute.
Explore asset pricing with liquidity risk and deep learning for Mean Field Games in finance, featuring talks by early career researchers on equilibrium models and computational methods.
Explore Coupled Physics Imaging with Otmar Scherzer, focusing on Photoacoustics and related mathematical inverse problems in this SIAM-IS virtual seminar on reconstructions in advanced imaging techniques.
Exploring space-variant regularisation models for inverse imaging problems, focusing on Total Variation regularisation and its adaptive improvements for local image structures.
Explore entropic regularization in optimal transport with Marcel Nutz. Learn about convergence, local behavior, and applications in high-dimensional data problems.
Explore innovative approaches to solving turbulence in fluid dynamics using auxiliary functionals and sum-of-squares polynomial optimization, with applications to Kuramoto-Sivashinsky and Navier-Stokes equations.
Explore finite dimensional approximations of Hamilton-Jacobi-Bellman equations in probability measure spaces, focusing on convergence of viscosity solutions and representation formulas for limiting equations.
Exploring neural networks' role in imaging from sensor data, focusing on seismic applications like bandwidth extension and virtual source data generation for enhanced inversion techniques.
Explore low rank tensor completion methods using framelet, dictionary coding, deep plug-and-play prior, and more. Gain insights into theoretical and numerical results for solving complex imaging problems.
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