Showreel
Reel
Index
All clips 100
-
MUQ-SAC — Joint Arrhenius Uncertainty Quantification
Class A sampling: kappa scale, real UQ limits, fit quality per sample
-
MUQ-SAC — Joint Arrhenius Uncertainty Quantification
Class C sampling: kappa scale, real UQ limits, fit quality per sample
-
MUQ-SAC — Joint Arrhenius Uncertainty Quantification
Class D sampling: kappa scale, real UQ limits, fit quality per sample
-
MUQ-SAC — Joint Arrhenius Uncertainty Quantification
Class B sampling: kappa scale, real UQ limits, fit quality per sample
-
MUQ-SAC — Joint Arrhenius Uncertainty Quantification
All four sampling-method classes, live, one frame
-
Neural ODEs and Transformations — A Self-Built Course
S001 What a Function Does to Space
-
Neural ODEs and Transformations — A Self-Built Course
S002 Smooth, Continuous, Invertible
-
Neural ODEs and Transformations — A Self-Built Course
S003 Topological Invariants
-
Neural ODEs and Transformations — A Self-Built Course
S004 Elementary Scalar Transforms
-
Neural ODEs and Transformations — A Self-Built Course
S005 Exp, Log and the Log-Scaler
-
Neural ODEs and Transformations — A Self-Built Course
S006 Statistical Transforms
-
Neural ODEs and Transformations — A Self-Built Course
S007 Trig and Hyperbolic Transforms
-
Neural ODEs and Transformations — A Self-Built Course
S008 Polar, Cylindrical, Spherical
-
Neural ODEs and Transformations — A Self-Built Course
S009 Curvilinear Coordinates
-
Neural ODEs and Transformations — A Self-Built Course
S010 Linear Maps
-
Neural ODEs and Transformations — A Self-Built Course
S011 Homogeneous and Mobius Maps
-
Neural ODEs and Transformations — A Self-Built Course
S012 Polynomial Bases
-
Neural ODEs and Transformations — A Self-Built Course
S013 Fourier and the DFT
-
Neural ODEs and Transformations — A Self-Built Course
S014 Laplace and Resolvents
-
Neural ODEs and Transformations — A Self-Built Course
S016 PCA and Whitening
-
Neural ODEs and Transformations — A Self-Built Course
S017 Activation Functions
-
Neural ODEs and Transformations — A Self-Built Course
S018 Auditing a Transformation
-
Neural ODEs and Transformations — A Self-Built Course
S019 ODEs and Vector Fields
-
Neural ODEs and Transformations — A Self-Built Course
S020 Picard and Gronwall
-
Neural ODEs and Transformations — A Self-Built Course
S021 Linearization and Phase Portraits
-
Neural ODEs and Transformations — A Self-Built Course
S022 Stiffness and Arrhenius
-
Neural ODEs and Transformations — A Self-Built Course
S023 Forward Euler: Step Halving
-
Neural ODEs and Transformations — A Self-Built Course
S023 Forward Euler: Stability Blow-up
-
Neural ODEs and Transformations — A Self-Built Course
S024 RK4 Stages as Slope Arrows
-
Neural ODEs and Transformations — A Self-Built Course
S025 Absolute Stability Sweep
-
Neural ODEs and Transformations — A Self-Built Course
S026 Newton Inside a Backward Euler Step
-
Neural ODEs and Transformations — A Self-Built Course
S026 BDF Steps on the ROBER Simplex
-
Neural ODEs and Transformations — A Self-Built Course
S027 Adaptive Step Size Chasing Ignition
-
Neural ODEs and Transformations — A Self-Built Course
S028 Affine Normalization as Raw Reweighting
-
Neural ODEs and Transformations — A Self-Built Course
S029 SGD and Adam in Raw and Normalized Coordinates
-
Neural ODEs and Transformations — A Self-Built Course
S030 Log-Scaler Dead Zone: clamp_min against add_eps
-
Neural ODEs and Transformations — A Self-Built Course
S031 The Price of Eigenvalue Compression
-
Neural ODEs and Transformations — A Self-Built Course
S032 Gradient Flow Across Depth as the Gain Sweeps
-
Neural ODEs and Transformations — A Self-Built Course
S033 Depth as Time: Residual Blocks Against the Flow
-
Neural ODEs and Transformations — A Self-Built Course
S034 Neural ODE Training Trajectories
-
Neural ODEs and Transformations — A Self-Built Course
S035 Re-integrating the State Backwards
-
Neural ODEs and Transformations — A Self-Built Course
S036 Two routes to the gradient: the mismatch shrinks with the step
-
Neural ODEs and Transformations — A Self-Built Course
S037 Augmented Neural ODE: Rings Flow
-
Neural ODEs and Transformations — A Self-Built Course
S038 Regularizing Neural ODE dynamics: paths straighten as the Jacobian weight grows
-
Neural ODEs and Transformations — A Self-Built Course
S039 Stiff Neural ODE on ROBER: training with backward Euler in the loop
-
Neural ODEs and Transformations — A Self-Built Course
S040 ChemNODE-style training on H2/air autoignition: a held-out condition
-
Neural ODEs and Transformations — A Self-Built Course
S041 Single shooting flattens out; multiple shooting follows the oscillation
-
Neural ODEs and Transformations — A Self-Built Course
S042 A learned flow map rolled out on a held-out ignition
-
Neural ODEs and Transformations — A Self-Built Course
S043 Hölder means: which channel the gradient pushes on as the exponent changes
-
Neural ODEs and Transformations — A Self-Built Course
S044 A model of OH with a Sobolev term: value, time derivative and gradient share through training
-
Neural ODEs and Transformations — A Self-Built Course
S045 The Mahalanobis ellipse of two correlated errors as the shrinkage is removed
-
Neural ODEs and Transformations — A Self-Built Course
S046 Re-drawing a split until it looks good: what a gate would report
-
Neural ODEs and Transformations — A Self-Built Course
S047 A continuous normalizing flow carries a Gaussian to the two-moons data
-
Neural ODEs and Transformations — A Self-Built Course
S048 160 starting points fall onto the slow manifold of the Davis-Skodje model
-
Neural ODEs and Transformations — A Self-Built Course
S049 Sparse regression: the threshold sweeps from 12 terms to the exact 8-term support
-
Neural ODEs and Transformations — A Self-Built Course
S050 The nine Jacobian eigenvalues of a hydrogen/air ignition against the RK4 stability region
-
Neural ODEs and Transformations — A Self-Built Course
S051 The decoded temperature of a held-out ignition during training in four state charts
-
Neural ODEs and Transformations — A Self-Built Course
S052 72 training runs through a pilot check: who passes at each epoch, and who ends well
-
Turbulence Closures — From Mixing Length to Data-Driven RANS
Turbulence video: freely-decaying 2D vorticity field evolution
-
Turbulence Closures — From Mixing Length to Data-Driven RANS
Instrument Panel: synchronized field/spectrum/time-series dashboard (invented technique)
-
Turbulence Closures — From Mixing Length to Data-Driven RANS
Scale Telescope: sweeping a band-pass window through wavenumber space (invented technique)
-
Turbulence Closures — From Mixing Length to Data-Driven RANS
Closure Divergence Theatre: two SGS models, identical initial condition, watched diverging (invented technique)
-
Turbulence Closures — From Mixing Length to Data-Driven RANS
Backscatter Flash Map: spatial structure of upscale energy transfer (invented technique)
-
Turbulence Closures — From Mixing Length to Data-Driven RANS
Pipeline.Animation: a movie declared, not hand-scripted
-
Turbulence Closures — From Mixing Length to Data-Driven RANS
Bluff-body wake: vorticity animation
-
flamelab
All four regimes at once -- multi-location width tracking, one frame
-
dokimazo — A PIDO Optimization Workbench
Conformer search optimization process — n-dodecane relaxing toward its lowest-energy shape
-
dokimazo — A PIDO Optimization Workbench
Five solvers racing to the Rosenbrock minimum, same evaluation budget
-
dokimazo — A PIDO Optimization Workbench
The same five solvers on Rastrigin, a highly multimodal landscape
-
dokimazo — A PIDO Optimization Workbench
Search trajectory over a genuine 3-decision-variable problem
-
dokimazo — A PIDO Optimization Workbench
Rosenbrock: watch the search itself, not a spinning camera
-
dokimazo — A PIDO Optimization Workbench
Himmelblau: the same search, four equal minima to choose from
-
dokimazo — A PIDO Optimization Workbench
The vine mark: "I am the vine, you are the branches" (John 15:5) as a real topology optimization
-
dokimazo — A PIDO Optimization Workbench
"Tested by fire" (1 Peter 1:7): a real constrained combustion optimization
-
dokimazo — A PIDO Optimization Workbench
Rectangle to airfoil: a real free-form camber-shape optimization, gradient-driven
-
Math Visual Studio
Manim render: shells with a hole, strips thinning to the integral
-
Math Visual Studio
Recording from the Studio: Deform & Hair, wavy hair preset