
Explore Forward and Backward Euler integration methods for ODEs using Python and Matlab. Compare stability, error, and implementation on a spring-mass-damper system with analytic solutions.

Explore Forward and Backward Euler integration methods for ODEs, including derivations, error sources, and stability analysis. Gain insights into numerical integration techniques for solving differential equations.

Explore numerical integration of ODEs to analyze nonlinear systems and generate trajectories. Learn techniques for solving complex dynamics where analytic methods fall short.

Explore linearization of nonlinear systems around fixed points, demonstrated with a simple pendulum example using both manual calculations and MATLAB implementation.

Explore stability and equality cases in the Gaussian B-inequality, based on collaborative research with Livshyts, Rotem, and Volberg.

Explore toric principal bundles' classification, reduction, and stability in this mathematical lecture, delving into advanced concepts in algebraic geometry and group theory.

Explore analytic techniques in dynamics and geometry, focusing on the Calderón problem and its factorization through the Born approximation.

Explore Feigenbaum Henon maps structure in dynamical systems with Mikhail Lyubich's conference talk, part of a broad meeting celebrating Marcelo Viana's 60th birthday at IMPA.

Explore advanced filtering techniques for geometrically exact beam models using multisymplectic unscented Kalman filters in structural engineering applications.

Explore probabilistic ODE solvers with ProbNumDiffEq.jl. Learn Bayesian inference for numerical problems, implementation details, and future prospects in the Julia ecosystem.

Explore fluctuation limits in mean-field interacting nonlinear Hawkes processes, delving into advanced mathematical concepts and their applications.

Explore stability and asymptotic behavior of fronts in bidomain models with Hiroshi Matano's in-depth analysis and insights.

Explore dynamical systems and differential equations through intuitive examples. Learn key concepts like state variables, phase portraits, and limit cycles to understand how systems change over time.

Learn to rig a basic robot in Maya, focusing on creating controls for eyes, wheels, and body groups. Master essential techniques for character animation and control systems.

Learn character rigging in Blender 3D: Create a functional skeleton, set up controls, and prepare your 3D model for animation. Master essential techniques for bringing characters to life.

Learn advanced techniques for creating a realistic drifting car rig in 3ds Max, enhancing your 3D animation skills and bringing dynamic vehicle movements to life.

Explore how the human brain represents physical stability, from infant intuition to neural computations, and its applications in robotics and computer vision.

Explores recent findings on linear and nonlinear stability of shear flows and vortices in Euler equations, covering monotonic shear flows, point vortices, and smooth decreasing vortices.

Explore machine learning for nonlinear dynamical systems modeling, focusing on the SINDy algorithm and its applications in fluid dynamics, with emphasis on interpretable and physics-respecting solutions.

Explore computational principles of sensorimotor control, including optimal feedback control, state estimation, motor learning, and Bayesian decision theory in human movement and robotics.

Explore turbulent dynamics using Exact Coherent States, revealing coherent structures in experiments, forecasting turbulent evolution, and providing a geometric description of transient turbulence.