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Computational Quantum Physics
Covers variational methods and time-dependent principles in computational quantum physics.
Numerical Analysis: Nonlinear Equations
Covers algorithms for solving mathematical problems approximately using a computer, including nonlinear equations and numerical approximation methods.
Protein Structure Prediction
Delves into predicting protein structure through amino acid contact analysis and advanced computational methods.
Protein Design: Computational Methods
Covers challenges in protein design, energy functions, search algorithms, and applications in synthetic biology, emphasizing the importance of protein design and the methods used for designing proteins.
Stochastic Simulation: Fundamentals
Introduces stochastic simulation fundamentals, covering course organization, queueing models, finance, statistics, physics, and exam details.
Asymptotic Independence Models: Heffernan-Tawn Model
Explores the Heffernan-Tawn model for asymptotic independence and extreme events.
Advanced Analysis II: Differential Equations and Timers
Discusses advanced analysis concepts, focusing on differential equations and timers in microcontrollers.
Quantum Many-Body Dynamics: Artificial Neural Network Approach
Discusses simulating quantum many-body dynamics using artificial neural networks to overcome computational challenges and stabilize solutions.
Digital Humanities Workflow
Explores the workflow in Digital Humanities, emphasizing data collection and visualization.
Feedback Mechanisms in Visual Intelligence and Adaptation
Explores the significance of feedback mechanisms in visual intelligence and adaptation processes.
