Atomic Cluster Expansion for "Learning" Many-Body Interaction
Event Date:
2024-10-10T10:00:00
2024-10-10T11:00:00
Event Location:
AMPEL 311
Speaker:
Christoph Ortner, UBC Math department
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Intended Audience:
Graduate
Local Contact:
Mona Berciu
Event Information:
The integration of machine learning (ML) into the traditional modeling workflows is replacing decades-old - often ad hoc - approximations (e.g., in constitutive laws) leading to new models that far outstrip their predecessors in accuracy and transferability. ”Pure” ML approaches are rarely successful but remarkable results can be achieved when integrated with domain knowledge. I will introduce a general formalism, the Atomic Cluster Expansion, for parameterizing many-body interaction and how it can be used for reduced-order modelling. Examples are taken from interatomic potentials, coarse-grained MD, and VMC.
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2024-10-10T10:00:00
2024-10-10T11:00:00
Atomic Cluster Expansion for "Learning" Many-Body Interaction
Event Information:
The integration of machine learning (ML) into the traditional modeling workflows is replacing decades-old - often ad hoc - approximations (e.g., in constitutive laws) leading to new models that far outstrip their predecessors in accuracy and transferability. ”Pure” ML approaches are rarely successful but remarkable results can be achieved when integrated with domain knowledge. I will introduce a general formalism, the Atomic Cluster Expansion, for parameterizing many-body interaction and how it can be used for reduced-order modelling. Examples are taken from interatomic potentials, coarse-grained MD, and VMC.
Event Location:
AMPEL 311