Large Steklov Eigenvalues Under Geometric Constraints
Explore large Steklov eigenvalues in compact Riemannian manifolds, examining geometric constraints and constructing metrics with fixed volume and boundary conditions.
Dense Embeddings of Hyperbolic Manifold Groups
Explore dense embeddings of hyperbolic manifold groups, focusing on amalgamated products and linear Lie groups. Learn strategies to control properties of output embeddings.
Exponentially Many Graphs Are Determined by Their Spectrum
Explore discrete analogues of Kac's question on "hearing the shape of a drum" and learn about graphs determined by their spectrum in this mathematical seminar.
Hausdorff Dimension of Three-Dimensional Kakeya Sets
Explore groundbreaking research on Kakeya sets in R^3, uncovering a new lower bound for Hausdorff dimension and its implications in geometric measure theory.
Growth in Tensor Powers
Explore tensor power decomposition in group representations, focusing on asymptotic behavior and non-negligible summands using symmetric tensor category theory.
Curvature-Homogeneous Riemannian 3-Manifolds and Integrable Systems
Explore curvature-homogeneous Riemannian 3-manifolds, surveying known examples and recent discoveries. Delve into connections with integrable systems, particularly Toda lattices, to construct new explicit examples.
Asymptotic Orthogonality Relation for GL(n,R) - ICBS 2024
Explore generalized Dirichlet character orthogonality for GL(n,R), extending classical number theory to higher dimensions with applications.
Applications of Additive Combinatorics to Problems in Fractal Geometry
Explore applications of additive combinatorics in fractal geometry, focusing on self-similar sets with overlaps and recent advancements in the field.
The Singular Set of Stable Minimal Hypersurfaces
Explore stable minimal hypersurfaces, their singularities, and recent findings on constructing metrics with specific singular sets in higher dimensions.
Generic Dynamics of the Mean Curvature Flows
Explore generic dynamics of mean curvature flows, including perturbation of shrinkers and isolatedness of cylindrical singularities in hypersurface evolution.
Equiangular Lines and Eigenvalue Multiplicity - ICBS 2024
Explore equiangular lines in high dimensions, solving a longstanding problem using spectral graph theory and discussing future research directions.
Optimal Immersions in the Calculus of Variations of Surfaces
Explore innovative minmax techniques for optimal surface immersions, including recent progress on Yau, Willmore, and 16π conjectures in calculus of variations.
Total Positivity: Combinatorics, Geometry and Representation Theory
Explore total positivity theory in matrices, its applications, and recent developments in combinatorics, geometry, and representation theory.
Linear Stochastic Graphon Systems with Q-Noise
Explore linear stochastic graphon systems with Q-noise, extending classical theory to large networks. Learn about LQG control problems, finite rank operators, and Nash Equilibrium approximations in graphon-based systems.
Estimating Hausdorff Dimension via Iterated Function Schemes
Explore methods for estimating Hausdorff dimension using iterated function schemes, presented by Mark Pollicott from the University of Warwick.
Convergence Analysis and Parameter Choice for the Iterated Arnoldi-Tikhonov Method
Explore convergence analysis and parameter selection for the iterated Arnoldi-Tikhonov method in this mathematical conference talk by Lothar Reichel.
The Linear Algebra of Large Language Models
Explorez les fondements mathématiques des modèles de langage à grande échelle et leur lien avec l'algèbre linéaire avancée.
When is the Resolvent Like a Rank One Matrix? - Anne Greenbaum
Explore when the resolvent resembles a rank one matrix in this mathematical analysis of linear algebra concepts and applications.
PDEs and Stencils - SPARSE 2024
Explore PDEs and stencils in computational science, focusing on efficient numerical methods for solving partial differential equations.
Matrix Algebra for Engineers - Don't Be an Engineering Poser, Study Real Math
Discover a powerful book for engineers to master matrix algebra, enhancing mathematical skills crucial for real-world engineering applications and problem-solving.
Randomized Least Squares Optimization and its Incredible Utility for Large-Scale Tensor Decomposition
Explore randomized least squares optimization techniques for large-scale tensor decomposition, focusing on sublinear algorithms and their applications in data analysis.