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Lecture: Computing thermodynamic and transport properties using machine learning potentials
ICTP Condensed Matter and Statistical Physics
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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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Manuel Athenes - Thermodynamic & transport properties of metal alloys: thermoelasticity & diffusion
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HEDS | Computing Thermodynamic and Transport Properties of Water and Hydrogen Using ML Potentials
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Thermodynamic properties by on-the-fly machine-learned potentials within and beyond DFT
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Emine Küçükbenli - Atomistic modelling with Neural Network Potentials with PANNA
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Machine Learning Meets Molecular Dynamics: A Crash Course in MLIPs for Solids
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Christoph Schran - Machine learning potentials for complex aqueous systems made simple
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Carla Verdi: Thermodynamic Properties of Zirconia from Machine Learning within and beyond DFT
TACO: Taming Complexity in Materials Modeling
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