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Non-uniform random variate generation
Formal sciences
Statistics
Statistical inference
Bayesian statistics
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Related lectures (32)
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Random Numbers Visualization
Explains how constants affect the mean and variance of random numbers.
Probability Theory: Central Limit Theorem
Explores probability theory, distribution of averages, and the central limit theorem.
Markov Chains and Algorithm Applications
Covers the fundamentals of Markov chains and their applications in algorithms, focusing on proper coloring and the Metropolis algorithm.
Sampling: Continuous Spatial Phenomena
Covers different spatial sampling procedures and properties in Geographic Information Systems.
Signals & Systems I: Uncertainty Relations and Gaussian Impulse
Explores uncertainty relations, Gaussian impulse, pseudo-probability density, and Gabor functions in signals and systems.
Monte Carlo Method: Surface Radiative Exchange
Explores the Monte Carlo method for surface radiative exchange and its applications in emission, absorption, and reflection.
Normal Distribution: Characteristics and Examples
Covers the characteristics and importance of the normal distribution, including examples and treatment scenarios.
Errors in Sampling: Correlation and Time Analysis
Explores errors in sampling, correlation functions, time analysis, and blocking techniques.
Sparsest Cut: ARV Theorem
Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.
Notions of Probability: Central Limit Theorem
Covers basic probability theory and the central limit theorem for Gaussian distribution.
Statistical Analysis: Data Exploration and Inference
Covers statistical analysis, emphasizing data exploration and inference to quantify uncertainty and draw conclusions.
Monte Carlo Simulation: Lennard-Jones Liquid
Explores Monte Carlo simulation of a Lennard-Jones liquid and the importance of sampling through correlated sampling.
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