24:37
Neural ODEs (NODEs) [Physics Informed Machine Learning]
34:32
Physics Informed Neural Networks (PINNs) [Physics Informed Machine Learning]
21:28
SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
19:01
AI/ML+Physics: Preview of Upcoming Modules and Bootcamps [Physics Informed Machine Learning]
24:01
AI/ML+Physics: Recap and Summary [Physics Informed Machine Learning]
20:26
Using sparse trajectory data to find Lagrangian Coherent Structures (LCS) in fluid flows
32:35
AI/ML+Physics Part 5: Employing an Optimization Algorithm [Physics Informed Machine Learning]
12:22
The Future of Model Based Engineering: Collimator 2.0
23:12
AI/ML+Physics Part 4: Crafting a Loss Function [Physics Informed Machine Learning]
36:30
AI/ML+Physics Part 3: Designing an Architecture [Physics Informed Machine Learning]
36:11
AI/ML+Physics Part 2: Curating Training Data [Physics Informed Machine Learning]
43:27
AI/ML+Physics Part 1: Choosing what to model [Physics Informed Machine Learning]
47:27
Physics Informed Machine Learning: High Level Overview of AI and ML in Science and Engineering
16:10
Can we make commercial aircraft faster? Mitigating transonic buffet with porous trailing edges
19:14
A Neural Network Primer
11:46
Supervised & Unsupervised Machine Learning
13:48
A Machine Learning Primer: How to Build an ML Model
25:23
Arousal as a universal embedding for spatiotemporal brain dynamics
28:02
New Advances in Artificial Intelligence and Machine Learning
14:51
Nonlinear parametric models of viscoelastic fluid flows with SINDy
14:16
[5/8] Control for Societal-Scale Challenges: Road Map 2030 [Technology, Validation, and Transition]
10:19
[8/8] Control for Societal-Scale Challenges: Road Map 2030 [Recommendations]
11:39
[2/8] Control for Societal-Scale Challenges: Road Map 2030 [Societal Drivers]
09:16
[1/8] Control for Societal-Scale Challenges: Road Map 2030 [Introduction]
11:20
[6/8] Control for Societal-Scale Challenges: Road Map 2030 [Education]
10:46
[3/8] Control for Societal-Scale Challenges: Road Map 2030 [Technological Trends]
08:08
[7/8] Control for Societal-Scale Challenges: Road Map 2030 [Ethics, Fairness, & Regulatory Issues]
11:37
[4/8] Control for Societal-Scale Challenges: Road Map 2030 [Emerging Methodologies]
02:38
🤯🤯🤯 Integrating GPT-4 into Collimator.ai for Symbolic Modeling and Control** 🔥🔥🔥
10:36
New Book!!! Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
50:33
Complex Analysis L13: Bromwich Integrals and the Inverse Laplace Transform
21:34
Complex Analysis L12: Examples of Complex Integrals
13:42
Complex Analysis L11: Examples of Cauchy-Integral Formula
16:43
Complex Analysis L10: Cauchy Integral Formula
24:51
Complex Analysis L09: Complex Residues
41:29
Complex Analysis L08: Integrals in the Complex Plane
41:15
Complex Analysis L07: Analytic Functions Solve Laplace's Equation
43:49
Complex Analysis L06: Analytic Functions and Cauchy-Riemann Conditions
35:17
Complex Analysis L05: Roots of Unity and Rational Powers of z
28:01
Complex Analysis L04: The Complex Logarithm, Log(z)
25:20
Complex Analysis L03: Functions of a complex variable, f(z)
16:03
Complex Analysis L02: Euler's formula, one of the most important formulas in all of mathematics
29:23
Complex Analysis L01: Overview & Motivation, Complex Arithmetic, Euler's Formula & Polar Coordinates
32:11
Topics in Dynamical Systems: Fixed Points, Linearization, Invariant Manifolds, Bifurcations & Chaos
25:04
Solving PDEs with the Laplace Transform: The Wave Equation
40:16
Solving PDEs with the Laplace Transform: The Heat Equation
30:06
Moore's Law, exponential growth, and extrapolation!
44:01
Chaotic Dynamical Systems
20:01
Numerical Integration of Chaotic Dynamics: Uncertainty Propagation & Vectorized Integration
36:52
Coding a Fourth-Order Runge-Kutta Integrator in Python and Matlab
30:22
Runge-Kutta Integrator Overview: All Purpose Numerical Integration of Differential Equations
31:15
Numerical Integration of ODEs with Forward Euler and Backward Euler in Python and Matlab
33:26
Stability of Forward Euler and Backward Euler Integration Schemes for Differential Equations
12:06
Error Analysis of Euler Integration Scheme for Differential Equations Using Taylor Series
23:28
Deriving Forward Euler and Backward/Implicit Euler Integration Schemes for Differential Equations
23:49
Numerical Simulation of Ordinary Differential Equations: Integrating ODEs
19:00
Why we can't take "dt" to 0 in a computer: Sources of error in numerical differentiation
29:43
Numerical Integration: Discrete Riemann Integrals and Trapezoid Rule
42:16
Numerical Differentiation: Second Derivatives and Differentiating Data
36:57
Numerical Differentiation with Finite Difference Derivatives
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