Lectures related to Computational Molecular Design: Mathematical Theory, High Performance Computing, In Vivo Experiments

Computational Molecular Design

Explores Computational Molecular Design, focusing on Mathematical Theory, High Performance Computing, and In Vivo Experiments, with an emphasis on quantum chemistry and electron dynamics.

Sampling Algorithms for Constrained Systems

Explores sampling algorithms for constrained systems, emphasizing the work of Benedict Leimkuhler from the University of Edinburgh.

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Machine Learning for Solving PDEs: Random Feature Method

Explores the Random Feature Method for solving PDEs using machine learning algorithms to approximate high-dimensional functions efficiently.

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Periodic Table Elements and Assyr Abdulle's Contributions

Explores the periodic table of elements and Assyr Abdulle's significant contributions to numerical analysis.

Thermodynamics and Energetics I

Explores fundamental thermodynamics concepts, laws, energy transfer, and system analysis.

Stochastic Differential Equations: Mean-Field Inference

Explores inference for stochastic differential equations, focusing on numerical methods and convergence analysis.

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