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Both methods provide a rich source of information but are also time-consuming and costly.
Congruence methods provide a useful tool in determining the number of solutions to a Diophantine equation.
Gradient-based methods provide a clear convergence criterion.
These methods provide a series of complementary, non-destructive measurements of surface properties.
Nevertheless, both methods provide a reasonably good trade-off between robustness and computational complexity.
Nonparametric density estimation (NPDE) methods provide a new idea and solution to these problems.
However, empirical methods provide a probabilistic, not conceptual, explanation of the analyzed linguistic phenomena.
These two methods provide a new approach for determining χ for strongly immiscible polymers.
Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity.
Ensemble methods provide a way to learn from data more accurately.
Probabilistic methods provide a means of demonstrating the potential variability in predictions of coastal cliff recession.
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