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That means our approach performs much more stably under noisy circumstances.
For biologically relevant configurations of the model, our quantitative study shows that a coupling approach performs much better than a decoupling one.
It is evident from the result that our approach performs much better in terms of space saving in terms of solving the NULL value problem as compared to other multi-tenant approaches.
When using a banded channel matrix approximation, the frequency-domain approach performs much better than the time-domain approach because we have ε<1 for this type of channel.
Results indicate that, when the number of equalizer taps is small (e.g., 3 taps) and the normalized recording density is high, the IIR equalizer designed based on the minimum mean-squared error approach performs much better than the FIR equalizer, especially in longitudinal recording channels.
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(We also tested the ML approach on a different data set of 4 measurements which was created without randomness in the measurement times: the ML approach performed much better in this case since the estimated parameters varied around the true values; data not shown).
All sparsity-driven approaches perform much more stably, yielding high TBR up to 20 dB regardless of the decreasing SNR.
In the case of Type I censoring, the MMLE approach also performs much better than regular MLE.
We observed that hybrid approach2 performed much better than any other approaches developed in this study for predicting aaRSs (figure 3 and table 2).
In comparison with the network condition approach, this method performs much better, but the solution to implement it is much more complex.
We found that for the figure ranking task different articles favor different approaches quite differently, and some approach can perform much better or much worse on certain subsets of articles, implying that a customized figure ranking model should be considered to address the challenging diversity of bioscience articles.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com