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Related lectures (27)

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Turbulent Caminar Visualization

Explores turbulent caminar visualization, current lines, and the significance of turbulence in classical physics and research.

Continuous Random Variables

Covers continuous random variables, probability density functions, and distributions, with practical examples.

Fundamental Limits of Gradient-Based Learning

Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.

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Collisionless Boltzmann Equation

Explores the Collisionless Boltzmann equation, distribution functions, Jeans theorems, resonances, chaotic orbits, and equilibria in stellar systems.

Normal Distribution: Properties and Calculations

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.

Causal Systems & Transforms: Delay Operator Interpretation

Covers z Variable as a Delay Operator, realizable systems, probability theory, stochastic processes, and Hilbert Spaces.

Martingales and Brownian Motion: Reflection Principle

Explores the reflection principle in martingales and Brownian motion, simplifying probability calculations.

From Boltzmann to Vlasov equation

Discusses the derivation of Vlasov equation from Boltzmann equation, conservation laws, and formal solutions.

Random Vectors & Distribution Functions

Covers random vectors, joint distribution, conditional density functions, independence, covariance, correlation, and conditional expectation.