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Related lectures (32)

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Ceramics: Powder Characterization

Explores the characterization of powders in ceramics, emphasizing the impact on ceramic properties and the manufacturing process.

The Sampling Theorem

Covers the sampling theorem, impulse train sampling, bandlimited signals, and the Nyquist rate.

Implementation of Sampling and Quantization

Covers the generation of signals with noise, sampling, and conversion to digital.

Monte Carlo Techniques: Sampling and Simulation

Explores Monte Carlo techniques for sampling and simulation, covering integration, importance sampling, ergodicity, equilibration, and Metropolis acceptance.

Generative Models: Crash Course

Offers a crash course on generative models, covering exponential families, sampling methods, and Metropolis algorithm.

Graph Coloring: Theory and Applications

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Sampling Signals: Stroboscopic Effect (Spectrum Folding)

Covers the consequences of undersampling signals and the stroboscopic effect.

Data Representations and Processing in Machine Learning

Covers data representations and processing techniques essential for effective machine learning algorithms.

Supercentenarians: Longevity Database Analysis

Covers the analysis of supercentenarians' longevity data and the impact of biased sampling.

Markov Chain Monte Carlo: Sampling and Convergence

Explores Markov Chain Monte Carlo for sampling high-dimensional distributions and optimizing functions using the Metropolis-Hastings algorithm.