Parameter Estimation for Deformable Objects

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Explores the Finite Element Method applied to linear statics of deformable solids.

Covers the derivation of exact results for small strains in composite materials and the implications of experimental data outside these limits.

Covers 3D linear elasticity, stress, strain, beams' behavior under loads, and torsion.

Explores Gaussian mixture models and denoising noisy signals using a probabilistic approach.

Introduces Fisher Information for parameter estimation based on collected data.

Explores Bayesian methods in choice modeling for personalized menu optimization and individual choice prediction.

Explores confidence intervals in statistics, covering construction, interpretation, and approximation methods.

Explores constitutive laws in elasticity theory, stress-deformation relationship, Hooke's laws, isotropy, and material symmetries.

Discusses Maximum Likelihood Estimation for Gaussian mean and variance, exploring parameter estimation in a Gaussian distribution.

Covers bias, variance, mean squared error, consistency, and maximum likelihood estimation in the Poisson model.