Justin Solomon
Associate professor, MIT Department of Electrical Engineering and Computer Science
http://people.csail.mit.edu/jsolomon/
Accessibility (for MIT-related content)
http://accessibility.mit.edu/
Numerical Algorithms for Computing & ML, fall 2025 (lecture 26): Leapfrog integration,adjoint method
Numerical Algorithms for Computing & ML, fall 2025 (lecture 25): Exponential/RK/Newmark integration
Numerical Algorithms for Computing & ML, fall 2025 (lecture 24): Ordinary differential equations
Numerical Algorithms for Computing & ML, fall 2025 (lecture 23): Numerical integrals and derivatives
Numerical Algorithms for Computing & ML, fall 2025 (lecture 22): 1D Quadrature/Numerical Integration
Numerical Algorithms for Computing & ML, fall 2025 (lecture 21): Interpolation
Numerical Algorithms for Computing & ML, fall 2025 (lecture 20): Alternating optimization and ADMM
Numerical Algorithms for Computing & ML, fall 2025 (lecture 19): Gauss-Newton, Levenberg-Marquardt
Numerical Algorithms for Computing & ML, fall 2025 (lecture 18): Conjugate gradient algorithm
Numerical Algorithms for Computing & ML, fall 2025 (lecture 17): Active set, barrier, intro to CG
Numerical Algorithms for Computing & ML, fall 2025 (lecture 16): Constrained optim., KKT conditions
Numerical Algorithms for Computing & ML, fall 2025 (lecture 15): BFGS and Quasi-Newton Methods
Numerical Algorithms for Computing & ML, fall 2025 (lecture 14): Convergence of gradient descent
Numerical Algorithms for Computing & ML, fall 2025 (lecture 13): Golden sec search, Wolfe conditions
Numerical Algorithms for Computing & ML, fall 2025 (lecture 12): Broyden's method, root finding
Numerical Algorithms for Computing & ML, fall 2025 (lecture 11): Procrustes problem, root finding
Numerical Algorithms for Computing & ML, fall 2025 (lecture 10): Re-deriving SVD, SVD applications
Numerical Algorithms for Computing & ML, fall 2025 (lecture 9): QR iteration, intro to SVD
Numerical Algorithms for Computing & ML, fall 2025 (lecture 7): Applications of eigenvalues
Numerical Algorithms for Computing & ML, fall 2025 (lecture 6): QR factorization
Numerical Algorithms for Computing & ML, fall 2025 (lecture 5): Condition number for linear systems
Numerical Algorithms for Computing & ML, fall 2025 (lecture 4): Cholesky factorization
Numerical Algorithms for Computing & ML, fall 2025 (lecture 3): LU factorization, least-squares
Numerical Algorithms for Computing & ML, fall 2025 (lecture 2): Conditioning, Gaussian elimination
Numerical Algorithms for Computing & ML, fall 2025 (lecture 1): Introduction, number systems
Shape Analysis, spring 2023 (lecture 3): Smooth curves
Lecture 5: Smooth and discrete surfaces (warning: camera broke!)
Shape Analysis, spring 2023 (lecture 21): More optimal transport
Shape Analysis, spring 2023 (lecture 7): Discrete curvature
Shape Analysis, spring 2023 (lecture 11): Structure-preserving embedding