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Related lectures (32)
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Graph Coloring: Theory and Applications
Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.
Fourier Transform and Sampling
Covers the Fourier transform of sampled signals, reconstruction, and harmonic response.
The Fréchet Embedding: Distortion D
Covers the Fréchet embedding with distortion D and its applications.
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.
Sampling Signals: Stroboscopic Effect (Spectrum Folding)
Covers the consequences of undersampling signals and the stroboscopic effect.
Transfer Functions and Control Algorithms
Explores transfer functions, control algorithms, and system transformations in discrete and analog systems, with practical exercises included.
Gibbs Sampling: Simulated Annealing
Covers the concept of Gibbs sampling and its application in simulated annealing.
Statistical Mechanical Resistance: Ceramics
Covers statistical mechanical resistance in ceramics, including Weibull statistic and stable cracking behavior in compression.
Sampling: Continuous Spatial Phenomena
Covers different spatial sampling procedures and properties in Geographic Information Systems.
Aggregation: Forecasting
Explores aggregation in choice models and techniques for handling large datasets.
Estimation Methods: BLP and Control-Function
Covers the inconsistency in estimates due to endogeneity and introduces the BLP and Control-Function estimation methods.
Diffusion: Data Denoising and Generative Modeling
Explores Data Denoising Diffusion Models, training objectives, sampling techniques, and challenges in applying diffusion to text.
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