MathWorks Math Modeling Challenge 2021 - Adlai E Stevenson High School Finalist Presentation
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.
MathWorks Math Modeling Challenge 2021 - Julia R Masterman Middle High School Finalist Presentation
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.
Entropic Optimal Transport - Eighteenth SIAM Activity Group on FME Virtual Talk
Explore entropic regularization in optimal transport with Marcel Nutz. Learn about convergence, local behavior, and applications in high-dimensional data problems.
E-Bike Future Prediction Model - M3 Challenge Finalist Presentation
High school team presents mathematical modeling solution predicting the future of E-Bikes in the U.S., showcasing innovative problem-solving skills and STEM application in a prestigious competition.
Bayesian Reimaging of Sparsity in Inverse Problems - SIAM-IS Virtual Seminar
Bayesian approach to sparse inverse problems in imaging and dictionary learning, featuring efficient computational framework and hierarchical prior models for sparsity promotion and automatic model reduction.
Immunology for Mathematicians
Explore mathematical approaches to immunology, including modeling immune responses and viral dynamics, in this lecture by renowned researcher Alan S. Perelson from Los Alamos National Laboratory.
Graph Algorithms and Coding - Session 5C
Explore advanced graph algorithms and coding techniques in this IEEE session, focusing on cutting-edge research and practical applications in computer science.
Graph Algorithms and Graph Theory - Session 1B
Explore advanced concepts in graph algorithms and theory, delving into cutting-edge research and applications presented at FOCS 2020.
Graph Algorithms and Graph Theory - Session 7A
Explore advanced concepts in graph algorithms and theory, delving into cutting-edge research and applications presented at the FOCS 2020 conference.
Counting Small Induced Subgraphs Satisfying Monotone Properties
Explore techniques for enumerating small induced subgraphs with specific properties, focusing on algorithmic approaches and complexity analysis in graph theory.
Efficient Truncated Statistics with Unknown Truncation
Explore efficient methods for analyzing truncated data with unknown truncation points, enhancing statistical inference in various fields of study.
New Notions and Constructions of Sparsification for Graphs and Hypergraphs
Explore innovative concepts and techniques for graph and hypergraph sparsification, advancing understanding of network structures and algorithms in computer science.
Cookbook Lower Bounds for Statistical Inference in Distributed and Constrained Settings - Part 2
Explore advanced statistical inference techniques for distributed and constrained environments, focusing on lower bounds and their applications in complex data analysis scenarios.
Discovering Emerging Open Source Communities Through Graphical Analysis
Explore graph theory techniques to visualize open source ecosystems, identify emerging communities, and uncover relationships between projects using centrality algorithms and the Augur OSS project.
Graph and Tensor Algorithmic Complexity - Unit 6, Module 5
Explore algorithmic complexity in graphs and tensors, focusing on computational approaches to causality and living systems from networks to cells.
A Gentle Introduction to Network Science - Dr Renaud Lambiotte, University of Oxford
Explore key properties and modeling tools for real-life networked systems across various domains, from biology to sociology, with Dr. Renaud Lambiotte's comprehensive overview of network science.
The Changing Role of National Statistics Offices in a Data-Driven Future - Professor Sir Ian Diamond
Exploring how national statistics offices innovate to meet modern data demands, utilizing new methods and sources for timely, accurate information to inform critical societal decisions.
Structured Dynamic Graphical Models & Scaling Multivariate Time Series
Explore advanced Bayesian methods for multivariate time series forecasting, focusing on scalability and model complexity. Learn about dynamic dependency networks and graphical dynamic linear models with real-world applications.
New Challenges in Computational Statistics
Explore cutting-edge computational statistics challenges and innovations in this lecture by Professor Gareth Roberts, focusing on complex data analysis and algorithm advancements in statistical science.
Stability and Inference for Position-Dependent Langevin Diffusions
Explore stability and inference in position-dependent Langevin diffusions, combining statistical inference, computation, and physical laws for complex systems modeling across various scientific domains.
Stratification for Markov Chain Monte Carlo
Explore advanced Markov Chain Monte Carlo techniques, focusing on stratification methods for complex systems modeling and statistical inference in various scientific domains.