Speaker: Professor Michele Ceriotti

Machine Learning at the Atomic Scale: From Structural Representations to Chemical Insights

When modeling materials and molecules at the atomic scale, achieving a realistic level of complexity and making quantitative predictions are usually conflicting goals. Data-driven techniques have made great strides towards enabling simulations of materials in realistic conditions with uncompromising accuracy. [more]
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