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2d ago
AI for molecular simulations may not need built-in physics to deliver strong results
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Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science. Classical machine learning approaches to molecular dynamics (MD) encode fundamental physical principles directly into their model architectures, most notably energy conservation and equivariance, the requirement that predicted forces remain consistent regardless of how a molecule is oriented in space. These so-called inductive biases have long been considered essential for r
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