Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Lecture

Combining GLEs and PIMD

Related lectures (55)

Efficient Stochastic Numerical Methods

Explores efficient stochastic numerical methods for modeling and learning, covering topics like the Analytical Engine and kinase inhibitors.

Molecular dynamics and integrators

Explores molecular dynamics, integrators, trajectory generation, and error monitoring in atomistic modeling.

Equilibrium GLE sampling

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

Sampling the Canonical Ensemble

Explores sampling the canonical ensemble, temperature fluctuations, extended Lagrangian, and Maxwell-Boltzmann distribution in molecular dynamics simulations.

Recovering dynamical properties: Path Integral Methods

Explores deconvolution of GLE spectra to predict and extract dynamical properties from MD.

Uncertainty Quantification for Coarse-Grained Molecular Dynamics

Delves into uncertainty quantification in molecular dynamics, focusing on aerospace materials, modeling decisions, and coarse-grained dynamics.

Generalized Langevin Equations

Explores Generalized Langevin Equations and their computational implications in molecular dynamics simulations, emphasizing the impact of noise details on particle trajectories.

Spatial Sampling: Concepts and Techniques

Covers spatial sampling in GIS, including autocorrelation, elevation models, and interpolation methods.

Explicit Stabilised Methods: Applications to Bayesian Inverse Problems

Explores explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems, covering optimization, sampling, and numerical experiments.

Determinantal Point Processes and Extrapolation

Covers determinantal point processes, sine-process, and their extrapolation in different spaces.

Path Integral Methods: Advanced Techniques

Explores advanced path integral methods in computational science, covering efficient sampling, colored noise, high-order integrals, and quantum thermostats.

Digital Signal Processing: Theory

Covers the theory of digital signal processing, including sampling, transformation methods, digitization, and PID controllers.

Langevin dynamics: Path Integral Methods

Covers Langevin dynamics, Fokker-Planck equation, solving the Langevin equation, and efficiency of Langevin sampling in molecular dynamics.

Non-equilibrium GLE sampling

Explores the Non-equilibrium GLE sampling method for atomistic modeling and discusses S-like thermostats, quantum thermostat, anharmonic systems, and zero-point energy leakage.

Natural Language Generation: Decoding & Training

Explores challenges in natural language generation, decoding algorithms, training issues, and reward functions.

Generative Models: Self-Attention and Transformers

Covers generative models with a focus on self-attention and transformers, discussing sampling methods and empirical means.

Estimation Methods: BLP and Control-Function

Covers the inconsistency in estimates due to endogeneity and introduces the BLP and Control-Function estimation methods.

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.

Generative Models: Boltzmann Machine

Covers generative models, focusing on Boltzmann machines and constrained maximization using Lagrange multipliers.

Molecular Dynamics Simulations

Explores potential energy surfaces in molecular dynamics simulations and the use of mixed quantum mechanical/molecular mechanical methods.