Propagation of Randomness Under the Flow of Nonlinear Dispersive Equations
Explore the propagation of randomness in nonlinear dispersive equations with Andrea R. Nahmod, delving into advanced mathematical concepts and their applications in this insightful lecture.
The Hamilton-Jacobi Equation: Past and Present
Explore the historical and contemporary significance of the Hamilton-Jacobi equation in mathematics with insights from Ryan Hynd of the University of Pennsylvania.
Structure Preservation in the Discretization of Partial Differential Equations
Explore structure preservation techniques in discretizing partial differential equations, enhancing numerical accuracy and stability in computational mathematics.
The Mathematics of Life - Making Diffusion Your Friend
Explore how diffusion processes in biology can be modeled mathematically, with insights from a leading expert in mathematical biology and biophysics.
Dynamics of Systems with Low Complexity
Explore low complexity dynamical systems, their patterns, and mathematical properties in this engaging lecture by renowned mathematician Bryna Kra at the Joint Mathematics Meetings.
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.
Tropical Geometry and Shallow Water Waves
Explore the fascinating intersection of tropical geometry and shallow water waves in this engaging lecture by Harvard mathematician Lauren Kiyomi Williams.
Numerical Modelling of Earthquake Ground Motion
Explore advanced discontinuous Galerkin methods for modeling seismic wave propagation in complex geological domains, addressing challenges in geometry representation and solution accuracy.
Oxford Calculus - Heat Equation Derivation
Comprehensive derivation of the Heat Equation from physical principles, including Liebniz Rule and Fourier's Law. Extends to 2D and 3D applications with interactive exercises for practice.
Oxford Mathematician Explains SIR Travelling Wave Disease Model for COVID-19
Explore the SIR Travelling Wave model for disease spread, focusing on COVID-19. Learn how population movement affects epidemic dynamics, including spread speed and severity, and the importance of social distancing measures.
Oxford Mathematician Explains SIR Disease Model for COVID-19
Explore the SIR disease model's application to COVID-19, covering its derivation, spread prediction, peak infection, and total cases. Learn how social distancing impacts these factors.
Probabilistic Numerical Computation - A New Concept?
Explore probabilistic numerics, a new field combining mathematics, statistics, and computer science to quantify uncertainty in numerical methods for complex data analysis and modeling.
Langevin Monte Carlo: Randomized Midpoint Method Revisited
Explore advanced Langevin Monte Carlo techniques, focusing on the Randomized Midpoint method's superior sampling error guarantees and recent improvements for high-dimensional target distributions.
What's the Point of Mathematics? - Mathematical Modeling Applications
Explore the real-world applications and significance of mathematics with Dr. Nira Chamberlain, a renowned expert in mathematical modeling across various industries.
Fractals and Multifractals in Geophysics - Lorenz Lecture
Explore fractals and their applications in geophysics with renowned mathematician Benoit Mandelbrot in this historic AGU Fall Meeting lecture from 2001.
Constrained Optimization Over Semirings
Explore complexity of constraint optimization over semirings, focusing on OptConf problem. Discover complexity results for various semirings and potential for SAT solver-based algorithms.
Modelling Embryo Elongation and Somitogenesis
Explore embryo elongation and somitogenesis modeling, focusing on developmental biology concepts and computational approaches to understand early vertebrate embryo formation.
Stability of Amenable Groups - Uncountably Many Examples and Connections to Dynamical Systems
Explore amenable group stability, uncountable examples, and dynamical systems connections in this advanced mathematics talk by Itamar Vigdorovich from the Weizmann Institute of Science.
Cancer - Introduction and Clinical Challenges by Sudha Sundar
Comprehensive overview of cancer, exploring its clinical challenges and introducing potential applications of machine learning in oncology research and patient care.
Promoting Data-Efficiency of Deep Learning for Dynamical Systems
Exploring data-efficient deep learning for dynamical systems using Euclidean symmetric neural networks, demonstrated on a 3D Slinky model for accelerated simulation and generalization.
PECANNs - Physics and Equality Constrained Artificial Neural Networks
Innovative approach to physics-informed neural networks using constrained optimization, addressing hyperparameter challenges and improving accuracy for scientific applications involving multi-dimensional PDEs.