Lectures related to Trade-offs in Data and Time

Explicit Stabilised Methods: Applications to Bayesian Inverse Problems

Explores explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems, covering optimization, sampling, and numerical experiments.

Finite Differences and Finite Elements: Variational Formulation

Discusses finite differences and finite elements, focusing on variational formulation and numerical methods in engineering applications.

Computational Geomechanics

Covers the basics of computational geomechanics, including poroelasticity, plasticity, and numerical methods for solving geotechnical problems.

L1 Regularization: Sparse Solutions and Dimensionality Reduction

Delves into L1 regularization, sparse solutions, and dimensionality reduction in the context of machine learning.

Numerical Differentiation: Part 1

Covers numerical differentiation, forward differences, Taylor's expansion, Big O notation, and error minimization.

Optimization with Constraints: KKT Conditions

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Optimization with Constraints: Theory and Applications

Covers the theory and applications of optimization with constraints, including key concepts and numerical methods.

Numerical Methods: Exercises

Covers exercises related to numerical methods, focusing on computational algorithms and problem-solving strategies.

Berni Alder Prize: Celebrating 50 Years of CECAM

Commemorates 50 years of CECAM and the Berni J. Alder CECAM Prize, covering milestones in computational methods, quantum mechanics, slip motion, and more.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Jupyter Notebooks for Numerical Analysis

Covers the transition to Python and Jupyter notebooks for Numerical Analysis at EPFL, including interactive exercises and graded tests.

Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

Mechanics of Slender Structure: Naturally Curly Hair in 3D Log in to Mediaspace to watch this video

Delves into the mechanics of slender structures using naturally curly hair in 3D as an example.

Convex Sets: MGT-418 Lecture Log in to Mediaspace to watch this video

On Convex Optimization covers course organization, mathematical optimization problems, solution concepts, and optimization methods.

Faster Gradient Descent: Projected Optimization Techniques Log in to Mediaspace to watch this video

Covers faster gradient descent methods and projected gradient descent for constrained optimization in machine learning.

Convex Sets: Mathematical Optimization Log in to Mediaspace to watch this video

Introduces convex optimization, covering convex sets, solution concepts, and efficient numerical methods in mathematical optimization.

Optimization Techniques: Convexity and Algorithms in Machine Learning Log in to Mediaspace to watch this video

Covers optimization techniques in machine learning, focusing on convexity, algorithms, and their applications in ensuring efficient convergence to global minima.

Numerical Integration: Order and Convergence Log in to Mediaspace to watch this video

Explores numerical integration order and convergence for accuracy in numerical methods.

Root Finding Methods: Bisection and Secant Techniques Log in to Mediaspace to watch this video

Covers root-finding methods, focusing on the bisection and secant techniques, their implementations, and comparisons of their convergence rates.

Numerical Analysis: Nonlinear Equations Log in to Mediaspace to watch this video

Covers algorithms for solving mathematical problems approximately using a computer, including nonlinear equations and numerical approximation methods.