Multivariate Portfolio Choice via Quantiles
Explore multivariate portfolio optimization using quantiles, extending univariate approaches to solve complex financial problems and develop new numerical solutions for multivariate preferences.
Reduced Form Setting Under Model Uncertainty With Nonlinear Affine Intensities - Prof Francesca Biagini
Explores reduced-form market models with financial assets and life insurance liabilities under model uncertainty, focusing on mortality intensities and longevity bonds. Discusses arbitrage-free pricing and contingent claims in this framework.
Assessing Asset-Liability Risk and the Numerical Approximation of Conditional Expectations
Explore asset-liability risk assessment and numerical approximation techniques for conditional expectations in quantitative finance, enhancing risk management skills.
Enhancing Scientific Computing Through Physics-Informed Neural Networks
Explore physics-informed neural networks (PINNs) as an alternative to traditional scientific computation, addressing challenges in high-dimensional problems and incorporating noisy data in inverse problems.
Newton's Method and Algebraic Curves - Real Numbers and Limits Math Foundations
Explore Newton's method for algebraic curves, examining Fermat curves and Bernoulli's Lemniscate. Learn about Taylor expansions, tangent planes, and iterative techniques for approximating curve intersections.
Vectorized Integration and the Lorenz Equation
Explore vectorized integration and the Lorenz equation, focusing on chaos, turbulence, and uncertainty in engineering mathematics, with practical MATLAB implementations.
Uncertainty Quantification of Quantum Chemical Methods - IPAM at UCLA
Explore uncertainty quantification in quantum chemistry, covering error estimation, benchmarking, and machine learning approaches for improved accuracy in computational methods.
Approximate Matrix Eigenvalues, Subspace Iteration With Repeated Random Sparsification
Explore efficient matrix eigenvalue approximation using subspace iteration and random sparsification, with applications in quantum chemistry and high-dimensional problems.
Mathematical Analysis and Numerical Methods for Inverse Scattering Problems
Explore mathematical analysis and numerical methods for inverse scattering problems, covering applications, challenges, algorithms, and recent progress in stability analysis and deep learning approaches.
Using Functions to Build Models - Math Teacher Professional Development
Hands-on exploration of mathematical modeling using real-world problems, connecting concepts across Math I to Calculus. Focuses on function creation, domain analysis, and student engagement techniques.
Convergent Semi-Lagrangian Methods for the Monge-Ampère Equation on Unstructured Grids
Explores semi-Lagrangian discretisation of Monge-Ampère operator on P1 finite element spaces, discussing challenges and solutions for numerical methods in solving Monge-Ampère equations, with applications in inverse reflector problems.
Axel Målqvist - Localization of Multiscale Problems
Explore multiscale problem-solving techniques, focusing on Local Orthogonal Decomposition for PDEs. Learn about convergence, high-contrast data, and applications to time-dependent problems.
Uncertainty Quantification for Kinetic Equations I
Overview of uncertainty quantification for kinetic equations, covering Monte Carlo methods, multi-fidelity techniques, and stochastic Galerkin particle methods. Explores computational challenges and recent advancements in the field.
Structured -In-Feasibility- Nonmonotone Operator Splitting in Nonlinear Spaces
Explore nonmonotone operator splitting in nonlinear spaces, covering optimization theory, convergence, and applications in harmonic analysis with Professor Russell Luke.
Numerical Methods for Scattering and Resonance Properties in Molecules and Solids
Explore numerical methods for discretizing continuum states in electronic structure, addressing scattering, photo-ionization, and resonances. Learn efficient computational techniques with applications in condensed matter physics and chemistry.
Uncertainty Quantification for Kinetic Equations II
Explore uncertainty quantification for kinetic equations, focusing on Monte Carlo methods, multi-fidelity approaches, and stochastic Galerkin particle techniques to address high-dimensional challenges.
Numerical Methods
Comprehensive exploration of numerical methods covering error analysis, linear systems, interpolation, differentiation, integration, and solving algebraic equations using various techniques.
Introduction to Theory and Numerics of Partial Differential Equations - Lecture 5
Explore numerical methods for solving partial differential equations, focusing on techniques essential for gravitational wave astronomy and computational relativity.
Introduction to Theory and Numerics of Partial Differential Equations - Lecture 2
Explore numerical methods for solving partial differential equations, focusing on techniques essential for gravitational wave astronomy and computational relativity.
Introduction to Theory and Numerics of Partial Differential Equations - Lecture 3
Explore numerical methods for solving partial differential equations, focusing on techniques essential for gravitational wave astronomy and computational relativity.
Introduction to Theory and Numerics of Partial Differential Equations - Lecture 1
Explore fundamental concepts and numerical techniques for solving partial differential equations, essential for modeling complex physical phenomena in gravitational-wave astronomy and astrophysics.