Shape Analysis, spring 2023 (lecture 11): Structure-preserving embedding
Justin Solomon
Shape Analysis, spring 2023 (lecture 11): Structure-preserving embedding
1:19:12
Shape Analysis, spring 2023 (lecture 7): Discrete curvature
Justin Solomon
Shape Analysis, spring 2023 (lecture 7): Discrete curvature
1:23:12
Shape Analysis, spring 2023 (lecture 21): More optimal transport
Justin Solomon
Shape Analysis, spring 2023 (lecture 21): More optimal transport
1:21:47
Lecture 5: Smooth and discrete surfaces (warning: camera broke!)
Justin Solomon
Lecture 5: Smooth and discrete surfaces (warning: camera broke!)
1:13:38
Shape Analysis, spring 2023 (lecture 3): Smooth curves
Justin Solomon
Shape Analysis, spring 2023 (lecture 3): Smooth curves
1:26:04
Shape Analysis, spring 2023 (lecture 1): Introduction
Justin Solomon
Shape Analysis, spring 2023 (lecture 1): Introduction
1:08:40
Shape Analysis, spring 2023 (lecture 20): Continuous normalizing flows, Intro to optimal transport
Justin Solomon
Shape Analysis, spring 2023 (lecture 20): Continuous normalizing flows, Intro to optimal transport
1:15:25
Shape Analysis, spring 2023 (lecture 4): Discrete curves
Justin Solomon
Shape Analysis, spring 2023 (lecture 4): Discrete curves
1:22:23
Shape Analysis, spring 2023 (lecture 6b): Curvature of surfaces
Justin Solomon
Shape Analysis, spring 2023 (lecture 6b): Curvature of surfaces
1:03:03
Shape Analysis, spring 2023 (lecture 24): Consistent Correspondence II
Justin Solomon
Shape Analysis, spring 2023 (lecture 24): Consistent Correspondence II
55:44
Shape Analysis, spring 2023 (lecture 15): Low-dimensional Applications of the Laplacian
Justin Solomon
Shape Analysis, spring 2023 (lecture 15): Low-dimensional Applications of the Laplacian
1:22:21
Shape Analysis, spring 2023 (lecture 18): Vector field theory
Justin Solomon
Shape Analysis, spring 2023 (lecture 18): Vector field theory
1:18:20
Shape Analysis, spring 2023 (lecture 19): Polyvectors, discrete vector fields
Justin Solomon
Shape Analysis, spring 2023 (lecture 19): Polyvectors, discrete vector fields
1:12:47
Shape Analysis, spring 2023 (lecture 23): Consistent correspondence I (camera broke)
Justin Solomon
Shape Analysis, spring 2023 (lecture 23): Consistent correspondence I (camera broke)
1:22:58
Shape Analysis, spring 2023 (lecture 22): Shape correspondence
Justin Solomon
Shape Analysis, spring 2023 (lecture 22): Shape correspondence
1:21:25
Shape Analysis, spring 2023 (lecture 12): Laplacians I
Justin Solomon
Shape Analysis, spring 2023 (lecture 12): Laplacians I
1:21:17
Shape Analysis, spring 2023 (lecture 10): Euclidean embedding
Justin Solomon
Shape Analysis, spring 2023 (lecture 10): Euclidean embedding
1:22:16
Shape Analysis, spring 2023 (lecture 16): Laplacians on point clouds, ML applications
Justin Solomon
Shape Analysis, spring 2023 (lecture 16): Laplacians on point clouds, ML applications
1:13:04
Shape Analysis, spring 2023 (lecture 17): Manifold optimization (mic broke...)
Justin Solomon
Shape Analysis, spring 2023 (lecture 17): Manifold optimization (mic broke...)
1:23:16
Shape Analysis, spring 2023 (lecture 6a): Data structures for meshes
Justin Solomon
Shape Analysis, spring 2023 (lecture 6a): Data structures for meshes
17:36
Shape Analysis, spring 2023 (lecture 14): Discretizing the Laplacian
Justin Solomon
Shape Analysis, spring 2023 (lecture 14): Discretizing the Laplacian
1:23:50
Shape Analysis, spring 2023 (lecture 13): Laplacians II
Justin Solomon
Shape Analysis, spring 2023 (lecture 13): Laplacians II
1:25:11
Shape Analysis, spring 2023 (lecture 2): Linear and Variational Problems
Justin Solomon
Shape Analysis, spring 2023 (lecture 2): Linear and Variational Problems
1:17:55
Shape Analysis, spring 2023 (lecture 7): Geodesic distances
Justin Solomon
Shape Analysis, spring 2023 (lecture 7): Geodesic distances
1:16:22
Shape Analysis, spring 2023 (lecture 8): Geodesic distance algorithms
Justin Solomon
Shape Analysis, spring 2023 (lecture 8): Geodesic distance algorithms
1:22:12
Applied Numerical Algorithms, fall 2023 (lecture 25): Leapfrog, adjoint method, neural ODE
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 25): Leapfrog, adjoint method, neural ODE
1:21:38
Applied Numerical Algorithms, fall 2023 (lecture 24): Trapezoid/exponential/Newmark integration
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 24): Trapezoid/exponential/Newmark integration
1:24:02
Applied Numerical Algorithms, fall 2023 (lecture 23): Numerical ODE, simple integrators
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 23): Numerical ODE, simple integrators
1:22:43
Applied Numerical Algorithms, fall 2023 (lecture 22): More quadrature, numerical differentiation
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 22): More quadrature, numerical differentiation
1:24:01
Applied Numerical Algorithms, fall 2023 (lecture 21): Quadrature in 1D
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 21): Quadrature in 1D
1:19:17
Applied Numerical Algorithms, fall 2023 (lecture 20): Interpolation
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 20): Interpolation
1:20:30
Applied Numerical Algorithms, fall 2023 (lecture 19): Alternation, ADMM, proximal methods
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 19): Alternation, ADMM, proximal methods
1:20:24
Applied Numerical Algorithms, fall 2023 (lecture 18): Nonlinear least-squares, alternation
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 18): Nonlinear least-squares, alternation
1:19:32
Applied Numerical Algorithms, fall 2023 (lecture 17): More conjugate gradients; preconditioning
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 17): More conjugate gradients; preconditioning
1:21:44
Applied Numerical Algorithms, fall 2023 (lecture 16): Constraints; intro to conjugate gradients
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 16): Constraints; intro to conjugate gradients
1:22:31
Applied Numerical Algorithms, fall 2023 (lecture 15): Constrained optimization, KKT conditions
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 15): Constrained optimization, KKT conditions
1:19:21
Applied Numerical Algorithms, fall 2023 (lecture 14): BFGS, DFP, Quasi-Newton optimization
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 14): BFGS, DFP, Quasi-Newton optimization
1:20:01
Applied Numerical Algorithms, fall 2023 (lecture 13): Gradient descent, line search
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 13): Gradient descent, line search
1:21:39
Applied Numerical Algorithms, fall 2023 (lecture 12): Broyden low-rank updates, 1D optimization
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 12): Broyden low-rank updates, 1D optimization
1:15:10
Applied Numerical Algorithms, fall 2023 (lecture 11): Root-finding, Newton's/Broyden's methods
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 11): Root-finding, Newton's/Broyden's methods
1:20:32
Applied Numerical Algorithms, fall 2023 (lecture 10): Applications of SVD; Procrustes problem
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 10): Applications of SVD; Procrustes problem
1:17:13
Applied Numerical Algorithms, fall 2023 (lecture 9): QR iteration, SVD
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 9): QR iteration, SVD
1:23:17
Applied Numerical Algorithms, fall 2023 (lecture 8): Eigenvalue iteration, deflation
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 8): Eigenvalue iteration, deflation
1:20:53
Applied Numerical Algorithms, fall 2023 (lecture 7): Applications of eigenvectors
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 7): Applications of eigenvectors
1:08:30
Applied Numerical Algorithms, fall 2023 (lecture 6): QR factorization
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 6): QR factorization
1:18:46
Applied Numerical Algorithms, fall 2023 (lecture 5): Condition number for linear systems
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 5): Condition number for linear systems
59:16
Applied Numerical Algorithms, fall 2023 (lecture 4): Cholesky factorization, sparse matrices
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 4): Cholesky factorization, sparse matrices
1:20:24
Applied Numerical Algorithms, fall 2023 (lecture 3): LU factorization, designing linear systems
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 3): LU factorization, designing linear systems
1:19:45
Applied Numerical Algorithms, fall 2023 (lecture 2): Conditioning, linear systems, Gaussian elim.
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 2): Conditioning, linear systems, Gaussian elim.
1:21:44
Applied Numerical Algorithms, fall 2023 (lecture 1): Introduction, number systems, measuring error
Justin Solomon
Applied Numerical Algorithms, fall 2023 (lecture 1): Introduction, number systems, measuring error
1:21:06
Introduction to Computer Graphics, Lecture 10: Ray casting II
Justin Solomon
Introduction to Computer Graphics, Lecture 10: Ray casting II
1:17:26
Introduction to Computer Graphics, Lecture 5: Hierarchical modeling
Justin Solomon
Introduction to Computer Graphics, Lecture 5: Hierarchical modeling
1:19:16
Introduction to Computer Graphics, Lecture 7: Particle systems
Justin Solomon
Introduction to Computer Graphics, Lecture 7: Particle systems
1:19:06
Introduction to Computer Graphics, Lecture 2: Cubic curves
Justin Solomon
Introduction to Computer Graphics, Lecture 2: Cubic curves
1:20:10
Introduction to Computer Graphics, Lecture 3: Curves and surfaces
Justin Solomon
Introduction to Computer Graphics, Lecture 3: Curves and surfaces
1:17:33
Introduction to Computer Graphics, Lecture 8: Cloth simulation
Justin Solomon
Introduction to Computer Graphics, Lecture 8: Cloth simulation
1:20:49
Introduction to Computer Graphics, Lecture 4: Transformations
Justin Solomon
Introduction to Computer Graphics, Lecture 4: Transformations
1:13:56
Introduction to Computer Graphics, Lecture 9: Ray casting
Justin Solomon
Introduction to Computer Graphics, Lecture 9: Ray casting
1:11:46
Introduction to Computer Graphics, Lecture 6: Animation: Skinning/enveloping
Justin Solomon
Introduction to Computer Graphics, Lecture 6: Animation: Skinning/enveloping
1:15:31
Introduction to Computer Graphics, Lecture 1: Introduction
Justin Solomon
Introduction to Computer Graphics, Lecture 1: Introduction
56:30
Introduction to Computer Graphics, Lecture 11: Ray tracing
Justin Solomon
Introduction to Computer Graphics, Lecture 11: Ray tracing
1:19:11
Introduction to Computer Graphics, Lecture 12: Ray tracing II
Justin Solomon
Introduction to Computer Graphics, Lecture 12: Ray tracing II
1:19:01
Introduction to Computer Graphics, Lecture 13: Shading
Justin Solomon
Introduction to Computer Graphics, Lecture 13: Shading
1:14:54
Introduction to Computer Graphics, Lecture 14: Texture mapping
Justin Solomon
Introduction to Computer Graphics, Lecture 14: Texture mapping
1:14:26
Introduction to Computer Graphics, Lecture 15: Antialiasing
Justin Solomon
Introduction to Computer Graphics, Lecture 15: Antialiasing
1:23:06
Introduction to Computer Graphics, Lecture 16: Global illumination
Justin Solomon
Introduction to Computer Graphics, Lecture 16: Global illumination
1:22:46
Introduction to Computer Graphics, Lecture 17: Rasterization
Justin Solomon
Introduction to Computer Graphics, Lecture 17: Rasterization
1:16:41
Introduction to Computer Graphics, Lecture 18: Rasterization II
Justin Solomon
Introduction to Computer Graphics, Lecture 18: Rasterization II
1:22:06
Introduction to Computer Graphics, Lecture 19: Shadow maps
Justin Solomon
Introduction to Computer Graphics, Lecture 19: Shadow maps
1:11:21
Introduction to Computer Graphics, Lecture 20: Color
Justin Solomon
Introduction to Computer Graphics, Lecture 20: Color
1:02:31
Introduction to Computer Graphics, Lecture 21: Image processing
Justin Solomon
Introduction to Computer Graphics, Lecture 21: Image processing
1:12:46
Introduction to Computer Graphics, Lecture 22: Output devices
Justin Solomon
Introduction to Computer Graphics, Lecture 22: Output devices
1:08:35
Pachelbel's Canon (cello quartet arr. Malte Meyn)
Justin Solomon
Pachelbel's Canon (cello quartet arr. Malte Meyn)
6:03
Shape Analysis (Lectures 14, extra content): A simple Laplacian on point clouds
Justin Solomon
Shape Analysis (Lectures 14, extra content): A simple Laplacian on point clouds
23:20
Shape Analysis (Lecture 2): Linear and variational problems
Justin Solomon
Shape Analysis (Lecture 2): Linear and variational problems
1:27:50
Shape Analysis (Lecture 22): Consistent correspondence and cycle consistency
Justin Solomon
Shape Analysis (Lecture 22): Consistent correspondence and cycle consistency
1:56:57
Shape Analysis (Lecture 18): Optimization on manifolds; retractions
Justin Solomon
Shape Analysis (Lecture 18): Optimization on manifolds; retractions
1:25:49
Shape Analysis (Lecture 7): Approximating Gaussian/mean/principal curvatures on triangle meshes
Justin Solomon
Shape Analysis (Lecture 7): Approximating Gaussian/mean/principal curvatures on triangle meshes
1:31:42
Shape Analysis (Lecture 3, extra content): First variation of arc length in R^n
Justin Solomon
Shape Analysis (Lecture 3, extra content): First variation of arc length in R^n
18:17
Shape Analysis (Lectures 13, extra content): Divergence of tangent vector fields
Justin Solomon
Shape Analysis (Lectures 13, extra content): Divergence of tangent vector fields
45:54
Shape Analysis (Lecture 9): Geodesic distance algorithms, fast marching
Justin Solomon
Shape Analysis (Lecture 9): Geodesic distance algorithms, fast marching
1:25:47
Shape Analysis (Lecture 6, extra content): First variation of surface area, mean curvature normal
Justin Solomon
Shape Analysis (Lecture 6, extra content): First variation of surface area, mean curvature normal
46:33
Shape Analysis (Lectures 16, extra content): Frame (octahedral/odeco) fields in volumes
Justin Solomon
Shape Analysis (Lectures 16, extra content): Frame (octahedral/odeco) fields in volumes
16:30
Shape Analysis (Lecture 16): Vector fields, Lie/covariant derivatives, frame fields
Justin Solomon
Shape Analysis (Lecture 16): Vector fields, Lie/covariant derivatives, frame fields
1:36:17
Shape Analysis (Lecture 20): Segmentation and clustering (k-means, Frechet means, normalized cuts)
Justin Solomon
Shape Analysis (Lecture 20): Segmentation and clustering (k-means, Frechet means, normalized cuts)
1:30:28
Shape Analysis (Lecture 2, extra content): Gentler variational (Gateaux) derivatives, cubic splines
Justin Solomon
Shape Analysis (Lecture 2, extra content): Gentler variational (Gateaux) derivatives, cubic splines
45:16
Shape Analysis (Lecture 19): Optimal transport
Justin Solomon
Shape Analysis (Lecture 19): Optimal transport
1:24:41
Shape Analysis (Lecture 4): Discrete differential geometry of polyline curves
Justin Solomon
Shape Analysis (Lecture 4): Discrete differential geometry of polyline curves
54:45
Shape Analysis (Lectures 17, extra content): Continuous normalizing flows
Justin Solomon
Shape Analysis (Lectures 17, extra content): Continuous normalizing flows
45:18
Shape Analysis (Lecture 21): Surface correspondence algorithms
Justin Solomon
Shape Analysis (Lecture 21): Surface correspondence algorithms
1:44:15
Shape Analysis (Lecture 6): Second fundamental form and surface curvature
Justin Solomon
Shape Analysis (Lecture 6): Second fundamental form and surface curvature
1:11:15
Shape Analysis (Lecture 11): Structure-preserving embedding (ISOMAP, LLE); manifold learning
Justin Solomon
Shape Analysis (Lecture 11): Structure-preserving embedding (ISOMAP, LLE); manifold learning
1:20:08
Shape Analysis (Lectures 12-13): The Laplacian operator on intervals, regions, graphs, and manifolds
Justin Solomon
Shape Analysis (Lectures 12-13): The Laplacian operator on intervals, regions, graphs, and manifolds
2:29:36
Shape Analysis (Lecture 1): Introduction
Justin Solomon
Shape Analysis (Lecture 1): Introduction
1:01:40
Shape Analysis (Lecture 17): Vector fields on triangle meshes
Justin Solomon
Shape Analysis (Lecture 17): Vector fields on triangle meshes
54:46
Shape Analysis (Lectures 22, extra content): Angular synchronization w/ eigenvectors/SDP, extensions
Justin Solomon
Shape Analysis (Lectures 22, extra content): Angular synchronization w/ eigenvectors/SDP, extensions
58:58
Shape Analysis (Lectures 14): Laplacian operators via first-order Galerkin finite elements (FEM)
Justin Solomon
Shape Analysis (Lectures 14): Laplacian operators via first-order Galerkin finite elements (FEM)
1:15:03
Shape Analysis (Lecture 15): Applications of the Laplacian in graphics, vision, and learning
Justin Solomon
Shape Analysis (Lecture 15): Applications of the Laplacian in graphics, vision, and learning
1:25:56
Shape Analysis (Lecture 5): Defining surfaces and (sub)manifolds; mesh data structures
Justin Solomon
Shape Analysis (Lecture 5): Defining surfaces and (sub)manifolds; mesh data structures
1:35:06
Shape Analysis (Lecture 10): Metric spaces and embeddings
Justin Solomon
Shape Analysis (Lecture 10): Metric spaces and embeddings
43:30