
Explore the interplay between differential operators and domain geometry in Euclidean space with Tatiana Toro's insightful lecture, the inaugural AMS Maryam Mirzakhani Lecture at JMM 2020.

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.

Explore macroscopic fluctuations in hard sphere gases, including deviations from the Boltzmann equation, central limit theorem, and large deviation bounds in the Boltzmann-Grad limit.

Explore the intricacies of non-smooth vector field flows in this advanced mathematics lecture by Camillo De Lellis, delving into complex theoretical concepts and their applications.

Explore the concept of periodicity in mathematics, its applications, and significance across various fields with expert insights from Gaston Mandata N'Guerekata.

Explore the mathematical intricacies of elliptic operators and systems, focusing on solution regularity in this advanced lecture by renowned mathematician Jill Pipher.

Explore stability indices for nonlinear waves and patterns in PDEs, focusing on Evans Function and Maslov Index approaches, their geometric interpretations, and recent advancements in complex problem analysis.

Learn to solve the Heat Equation, a fundamental PDE in calculus, with Oxford mathematician Dr Tom Crawford. Includes practice questions, interactive worksheets, and a free calculator app for comprehensive understanding.

Learn to solve partial differential equations using separable solutions with Oxford mathematician Dr Tom Crawford. Includes examples, practice worksheets, and links to a free calculator app for checking your work.

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.

Learn to solve first order separable differential equations using the separation of variables method, with worked examples and practice exercises from an Oxford mathematician.

Explore Variational Bayes as an efficient alternative to MCMC for solving inverse problems in PDEs, using sparse precision matrices and stochastic optimization for improved computational tractability.

Innovative approach to physics-informed neural networks using constrained optimization, addressing hyperparameter challenges and improving accuracy for scientific applications involving multi-dimensional PDEs.

Explore the physics behind "tears of wine" phenomenon, examining undercompressive shocks in thin films and their role in the formation of wine tears using mathematical modeling and analysis.

Explore quantum algorithms for solving differential equations, focusing on efficiency and applications in scientific computation.

Explore advanced techniques for detecting change-points in stochastic differential equations, focusing on sequential methods and their applications in statistical analysis.

Explore a challenging differential equation from the renowned Putnam exam, delving into advanced mathematical concepts and problem-solving techniques.

Innovative extension of deep solver for FBSDEs with jumps, using neural networks to tackle high-dimensional problems in option pricing and counterparty credit risk.

Explore an intriguing differential equation, delving into its unique properties and solution methods for a deeper understanding of mathematical concepts.

Explore p-adic Frobenius structures in differential equations, their connection to algebraic geometry, and their relation to p-adic zeta values in hypersurface families.

Explore conjectures and criteria for identifying differential equations from Gauss-Manin connections and hypergeometric Calabi-Yau varieties, with a focus on Heun and Painlevé VI equations.