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Related lectures (31)

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Continuous Random Variables

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

Robustness in Visual Intelligence

Explores robustness in visual intelligence, addressing distribution shifts, failure examples, and strategies for improvement.

Radiative Exchange: Specular View Factors

Covers specular view factors, radiative exchange, energy transfer, and numerical integration methods in thermal radiation.

Continuous Random Variables: Basic Ideas

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Brownian Motion: Fundamentals and Applications

Explores the fundamentals of Brownian motion, including particle positions and distribution functions.

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.

Collisionless Boltzmann Equation

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

Probability Distributions: Central Limit Theorem and Applications

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Causal Systems & Transforms: Delay Operator Interpretation

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

Do ImageNet Classifiers Generalize?

Examines the generalization of ImageNet classifiers, safety-critical applications, overfitting, and the reliability of machine learning models.