Lectures related to Sampling Algorithms for Constrained Systems

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

Explores Computational Molecular Design, emphasizing Mathematical Theory, High Performance Computing, and In Vivo Experiments.

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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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Thermodynamics and Energetics I

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

Periodic Table Elements and Assyr Abdulle's Contributions

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

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Stochastic Differential Equations: Mean-Field Inference

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

High Order PDE-Convergence: ADI-Type Integrators

Covers the convergence of high-order PDEs using ADI-type integrators for parabolic problems.

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.

Eigenvalues and Eigenvectors

Covers eigenvalues and eigenvectors in linear algebra.

Computer Simulation: Early Days and Monte Carlo Method

Explores the early days of computer simulation, focusing on the Monte Carlo method and its evolution in scientific research.

Functions: Parametric, Integrals, Multi-variable

Covers parametric functions, integrals, and the origin of plasticity in metals.

Linear Algebra: Unitary Operators

Delves into unitary operators, self-adjoint properties, and spectral theorems in linear algebra.

Linear Algebra: Subspaces and Transformations

Explores subspaces in linear algebra and transformations, including kernels and images of linear transformations.

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Quasi-Stationary Distribution: Molecular Dynamics Modeling

Explores the quasi-stationary distribution approach in molecular dynamics modeling, covering Langevin dynamics, metastability, and kinetic Monte Carlo models.

Linear Algebra: Subspaces and Combinations

Explores subspaces and linear combinations in linear algebra.

Equilibrium GLE sampling

Explores optimizing Equilibrium GLE sampling efficiency and custom-tailored thermostats in atomistic modeling.

Molecular dynamics under constraints

Explores molecular dynamics simulations under holonomic constraints, focusing on numerical integration and algorithm formulation.