Central Limit Theorems for Poisson Functionals - The Malliavin-Stein Approach
Explore central limit theorems in stochastic geometry using the Malliavin-Stein method, with applications to random point collections and the Online Nearest Neighbour Graph.
Dimer Models and Random Tilings - Part 1
Explore dimer models and random tilings with Cédric Boutillier. Learn about Kasteleyn's theory, combinatorial correspondences, and asymptotic methods for studying perfect matchings on lattices.
Pierre Calka- Close-Up on Random Convex Hulls
Explore random convex hulls, Hausdorff distance, and asymptotic expansions in this mathematical talk on geometric probability and stochastic geometry.
Statistics in Medicine - Introduction to Clinical Research Analysis
Explore key statistical concepts in clinical research, including descriptive and inferential statistics, confidence intervals, p-values, and various statistical tests used in medical studies.
Concentration Inequalities for Poisson U-Statistics
Explore concentration inequalities for Poisson U-statistics, their optimality, and applications in stochastic geometry models. Gain insights into Poisson functionals and their significance in geometric analysis.
Complexity of Sparse Linear Regression
Explore new methods for solving sparse linear regression, overcoming limitations of traditional approaches and exploiting structural properties of covariance matrices in machine learning and statistics.
Two-Sided Estimates for Operator ℓp to ℓq Norms of Random Matrices with IID Entries
Explore two-sided estimates for operator norms of random matrices, discussing proofs, examples, and open problems in this mathematical analysis of iid entries and their implications.
Limit Theorems for the Volumes of Small Codimensional Random Sections of Lpn-Balls
Explore central limit theorems for volumes of random sections in high-dimensional geometry, with insights on open questions and recent research developments.
Is It Easier to Count Communities Than Find Them?
Explore computational challenges in detecting community structures in random graphs, examining statistical and computational phase transitions, and the difficulty of inferring community properties.
Minimal Rank of Submatrices of Random Rectangular Matrices
Explore the minimal rank of square submatrices in random rectangular matrices, proving a conjecture on their behavior as matrix dimensions vary.
Random Walks on Group Extensions
Explore random walks on group extensions in this advanced mathematics lecture, covering Zariski dense subgroups and their applications in algebraic geometry and number theory.
How to Be More Productive Using Mathematics
Discover how mathematical concepts like Poisson distribution and vector calculus can boost your productivity, explained by an Oxford mathematician using real-world applications and advanced modeling techniques.
Statistical Considerations in Multilevel Mediation Analysis
Explore advanced statistical techniques for multilevel mediation analysis, focusing on methodological challenges and innovative solutions in complex hierarchical data structures.
Geometric Functionals of Polyconvex Excursion Sets of Poisson Shot Noise Processes
Explore geometric functionals of polyconvex excursion sets in Poisson shot noise processes, including asymptotics, variance bounds, and central limit theorems for intrinsic volumes.
Dimer Models and Random Tilings - Part 2
Explore dimer models, perfect matchings, and tilings with advanced mathematical tools. Delve into Kasteleyn's theory, combinatorial correspondences, and asymptotic methods for large-scale limits.
Sequential Change-point Detection in Stochastic Differential Equations
Explore advanced techniques for detecting change-points in stochastic differential equations, focusing on sequential methods and their applications in statistical analysis.
Fluctuations of Linear Eigenvalue Statistics in Sample Covariance Matrices - Tensor Product Data
Explore fluctuations in linear eigenvalue statistics of sample covariance matrices with tensor product data, comparing normal and uniform distributions on unit sphere.
Spectrum of Sparse Inhomogeneous Random Graphs
Explore the spectrum of sparse inhomogeneous random graphs, examining structural properties and applications in network science, probability theory, and statistical physics.
Path Convergence of Markov Chains on Large Graphs
Explore path convergence of Markov chains on large graphs, examining theoretical aspects and applications in network science, probability theory, and complex systems analysis.
Algorithms on Networks
Explore algorithms for network analysis, optimization, and control. Learn techniques for solving complex problems on graphs and networks, with applications in various fields.
Spin Systems on Spatial Random Graphs
Explore spin systems on spatial random graphs, examining their properties, dynamics, and applications in network science and statistical physics.