TabChange produces more proximal and valid counterfactuals on tabular data by relationship-based flipping or adversarial latent-space attribute removal compared to baselines on seven datasets.
Information-theoretic measurements of coupling between structure and dynamics in glass-formers
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abstract
We analyse the connections between structure and dynamics in two model glass-formers, using the mutual information between an initial configuration and the ensuing dynamics to compare the predictive value of different structural observables. We consider the predictive power of normal modes, locally favoured structures, and coarse-grained measurements of local energy and density. The mutual information allows the influence of the liquid structure on the dynamics to be analysed quantitatively as a function of time, showing that normal modes give the most useful predictions on short time scales while local energy and density are most strongly predictive at long times.
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TabChange: Precise Attribute Changes in Tabular Data
TabChange produces more proximal and valid counterfactuals on tabular data by relationship-based flipping or adversarial latent-space attribute removal compared to baselines on seven datasets.