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Explores inverse design optimization in geometric computing, covering topics such as deployable structures, material-aware design, and programmed materials.
Covers the basics of reinforcement learning, including Markov Decision Processes and policy gradient methods, and explores real-world applications and recent advances.
Introduces the importance of studying algorithms, presents a clever algorithm for calculating an arithmetic series, and discusses efficiency and correctness in algorithms.
Introduces state-of-the-art methods in optimization and simulation, covering topics like statistical analysis, variance reduction, and simulation projects.