Search alternatives:
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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Raw data.
Published 2025“…The remaining working conditions did not exhibit a significant difference. However, the observed decreasing trend was consistent with previously documented research. …”
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Leaves of the <i>atb’’αβγδ</i> plants under brushing-induced mechanical stress conditions.
Published 2024Subjects: -
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Geometric manifold comparison visualization
Published 2025“…While many tr-FC approaches have been proposed, most are linear approaches, e.g. computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
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552
Hyperparameter ranges
Published 2025“…While many tr-FC approaches have been proposed, most are linear approaches, e.g. computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
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553
Convolutional vs RNN context encoder
Published 2025“…While many tr-FC approaches have been proposed, most are linear approaches, e.g. computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
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All data points from Fig 2.
Published 2025“…Specifically, we observed that demyelination caused an impairment in the ability of PV interneurons to sustain high-frequency firing associated with a substantial decrease in Kv3-specific currents. …”
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559
All data points from Fig 5.
Published 2025“…Specifically, we observed that demyelination caused an impairment in the ability of PV interneurons to sustain high-frequency firing associated with a substantial decrease in Kv3-specific currents. …”
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560
All data points from Fig 8.
Published 2025“…Specifically, we observed that demyelination caused an impairment in the ability of PV interneurons to sustain high-frequency firing associated with a substantial decrease in Kv3-specific currents. …”