final fixes
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@@ -593,7 +593,7 @@ In practice, convolutional architectures have achieved strong performance on seq
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For example,~\citeauthor{lecun_convolutional_1998} showed that a simple Temporal Convolutional Network often outperforms canonical
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For example,~\citeauthor{lecun_convolutional_1998} showed that a simple Temporal Convolutional Network often outperforms canonical
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recurrent models (like LSTMs) across diverse sequence modeling benchmarks.
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recurrent models (like LSTMs) across diverse sequence modeling benchmarks.
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Their experiments suggest that CNNs are “a natural starting point for sequence modeling,”
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Their experiments suggest that CNNs are “a natural starting point for sequence modeling,”
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especially when temporal features are local or multi-scale.
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especially when temporal features are local or multiscale.
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In summary, 1D convolutions provide an efficient way to extract local temporal features and compress high-resolution sequences,
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In summary, 1D convolutions provide an efficient way to extract local temporal features and compress high-resolution sequences,
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complementing recurrent and attention-based models in time-series analysis
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complementing recurrent and attention-based models in time-series analysis
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@@ -12,7 +12,7 @@ At the same time, many individuals seek alternatives to hormonal contraception,
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Accurate fertility prediction thus carries implications not only for individual reproductive autonomy,
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Accurate fertility prediction thus carries implications not only for individual reproductive autonomy,
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but also for public health, demographic trends, and the development of safe, data-driven fertility support tools.
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but also for public health, demographic trends, and the development of safe, data-driven fertility support tools.
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While textbooks often describe a menstrual cycle as lasting 28 to 30 days with ovulation around day 14~\cite{owen_physiology_nodate},
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While textbooks often describe a menstrual cycle as lasting 28 to 30 days with ovulation around day 14~\cite{owen_physiology_1975},
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such regularity is the exception rather than the rule~\cite{munster_length_1992, bull_real-world_2019}.
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such regularity is the exception rather than the rule~\cite{munster_length_1992, bull_real-world_2019}.
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For individuals with consistent cycle patterns, simple calendar-based predictions may suffice.
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For individuals with consistent cycle patterns, simple calendar-based predictions may suffice.
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However, for the majority, especially with increasing age and associated irregularity, more sophisticated methods are necessary.
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However, for the majority, especially with increasing age and associated irregularity, more sophisticated methods are necessary.
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