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Showing 961 - 980 results of 13,729 for search '(( significantly increased decrease ) OR ( significant ((greater decrease) OR (small decrease)) ))*', query time: 0.51s Refine Results
  1. 961
    Convolutional vs RNN context encoder

    Convolutional vs RNN context encoder by Eloy Geenjaar (21533195)

    Published 2025
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  2. 962
    The influence of training-time noise on classification accuracy and reliability

    The influence of training-time noise on classification accuracy and reliability by Eloy Geenjaar (21533195)

    Published 2025
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  3. 963
    Data sample demographics. Note that AP refers to anti-psychotic medication, and AD refers to anti-depressive medication. Thus, AP and AD in this table refer to the percentage of patients taking anti-psychotic and anti-depressive medication, respectively. PANSS is a symptom scale for schizophrenia. We show its positive, negative, and composite scores.

    Data sample demographics. Note that AP refers to anti-psychotic medication, and AD refers to anti-depressive medication. Thus, AP and AD in this table refer to the percentage of pa... by Eloy Geenjaar (21533195)

    Published 2025
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  4. 964
    An abstract depiction of our model, for the independent version of the model, the context representation is not concatenated inside the local encoder.

    An abstract depiction of our model, for the independent version of the model, the context representation is not concatenated inside the local encoder. by Eloy Geenjaar (21533195)

    Published 2025
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  5. 965
    These subfigures show a visualization of the context embeddings for the DSVAE model with LS=2=4,CS=2. The first subfigure from the left shows three patient clusters, the second subfigure both patients and controls, the third colors context embeddings based on the subject’s age, and the last subfigure colors the context embeddings based on the subject’s cognitive score, CMINDs.

    These subfigures show a visualization of the context embeddings for the DSVAE model with LS=2=4,CS=2. The first subfigure from the left shows three patient clusters, the second sub... by Eloy Geenjaar (21533195)

    Published 2025
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  6. 966
    The window classification accuracy for two of our proposed models (DSVAE, IDSVAE), windowed FNC (wFNC), and two baseline methods: context-only (CVAE), and local-only (LVAE).

    The window classification accuracy for two of our proposed models (DSVAE, IDSVAE), windowed FNC (wFNC), and two baseline methods: context-only (CVAE), and local-only (LVAE). by Eloy Geenjaar (21533195)

    Published 2025
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  7. 967
    The three schizophrenia patient clusters visualized using functional connectivity matrices. To create the visualizations, we take all the windows belonging to a cluster and average their wFNC matrix.

    The three schizophrenia patient clusters visualized using functional connectivity matrices. To create the visualizations, we take all the windows belonging to a cluster and average... by Eloy Geenjaar (21533195)

    Published 2025
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  8. 968
    The growth of co-transformed cells in the peritoneal cavity alters viral gene expression to mirror that of PEL cell lines.

    The growth of co-transformed cells in the peritoneal cavity alters viral gene expression to mirror that of PEL cell lines. by Mitchell Hayes (5334887)

    Published 2025
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  9. 969
    The growth of co-transformed cells in the peritoneal cavity alters their cellular gene expression to mirror that of PEL biopsies.

    The growth of co-transformed cells in the peritoneal cavity alters their cellular gene expression to mirror that of PEL biopsies. by Mitchell Hayes (5334887)

    Published 2025
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  10. 970
    Co-infected cells express both KSHV and EBV genes <i>in vitro</i> necessary for their survival and growth.

    Co-infected cells express both KSHV and EBV genes <i>in vitro</i> necessary for their survival and growth. by Mitchell Hayes (5334887)

    Published 2025
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  11. 971
    Analysis of FROM dynamics (pre-epidemic).

    Analysis of FROM dynamics (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  12. 972
    Analysis of FROM dynamics (post epidemic).

    Analysis of FROM dynamics (post epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  13. 973
    Robustness check.

    Robustness check. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  14. 974
    Third.

    Third. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  15. 975
    Analysis of TO dynamics (in-epidemic).

    Analysis of TO dynamics (in-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  16. 976
    Analysis of TO dynamics (pre-epidemic).

    Analysis of TO dynamics (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  17. 977
    Descriptive statistical analysis of the total sample.

    Descriptive statistical analysis of the total sample. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  18. 978
    Second.

    Second. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  19. 979
    Dynamics of net spillage in the first stage (pre-epidemic).

    Dynamics of net spillage in the first stage (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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  20. 980
    Dynamics of net spillage in the third stage (post epidemic).

    Dynamics of net spillage in the third stage (post epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
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