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Basic Notions: Computing thermodynamic and transport properties using machine learning potentials
ICTP Condensed Matter and Statistical Physics
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Lecture: Computing thermodynamic and transport properties using machine learning potentials
ICTP Condensed Matter and Statistical Physics
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1:12:43
HEDS | Computing Thermodynamic and Transport Properties of Water and Hydrogen Using ML Potentials
Inside Livermore Lab
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26:49
Thermodynamic properties by on-the-fly machine-learned potentials within and beyond DFT
Cambridge Materials
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1:14:21
48:17
Manuel Athenes - Thermodynamic & transport properties of metal alloys: thermoelasticity & diffusion
Institute for Pure & Applied Mathematics (IPAM)
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1:03:32
Emine Küçükbenli - Atomistic modelling with Neural Network Potentials with PANNA
mlip-workshop-2021
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Machine Learning Meets Molecular Dynamics: A Crash Course in MLIPs for Solids
Atoms to Materials
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Christoph Schran - Machine learning potentials for complex aqueous systems made simple
mlip-workshop-2021
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Wasserstein Distance & Optimal Transport — Fully Explained
The Synthetic Mind
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58:08
"Optimal Transport for Statistics and Machine Learning" Prof. Philippe Rigollet, MIT
Center for Intelligent Systems CIS EPFL
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32:57