Search alternatives:
significantly alter » significantly altered (Expand Search), significantly smaller (Expand Search), significantly better (Expand Search)
linear decrease » linear increase (Expand Search)
alter decrease » larger decrease (Expand Search), water decreases (Expand Search), teer decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
significantly alter » significantly altered (Expand Search), significantly smaller (Expand Search), significantly better (Expand Search)
linear decrease » linear increase (Expand Search)
alter decrease » larger decrease (Expand Search), water decreases (Expand Search), teer decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
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General technical specification for GW154/6700.
Published 2025“…Understanding spatial-temporal characteristics of wind speed is significant in meteorology, coastal engineering design and maritime industries. …”
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The impact of UV360 on the viability and developmental progression of zebrafish embryos.
Published 2025Subjects: -
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The impact of UV360 on the development of spinal motor neuron axons in zebrafish larvae.
Published 2025Subjects: -
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The impact of UV360 on the neurophysiological activity of zebrafish larvae.
Published 2025Subjects: -
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Geometric manifold comparison visualization
Published 2025“…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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Hyperparameter ranges
Published 2025“…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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297
Convolutional vs RNN context encoder
Published 2025“…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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