Search Results - "Leonarduzzi, R."

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  1. 1

    Deep Learning Abilities to Classify Intricate Variations in Temporal Dynamics of Multivariate Time Series by Liotet, P., Abry, P., Leonarduzzi, R., Senneret, M., Jaffres, L., Perrin, G.

    “…The aim of this work is to investigate the ability of deep learning (DL) architectures to learn temporal dynamics in multivariate time series. The methodology…”
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    Conference Proceeding
  2. 2

    Extending multifractal analysis to negative regularity: P-exponents and P-leaders by Leonarduzzi, R., Wendt, H., Jaffard, S., Roux, S. G., Torres, M. E., Abry, P.

    “…Scale invariance is a widely used concept to analyze real-world data from many different applications and multifractal analysis has become the standard…”
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    Conference Proceeding
  3. 3

    Dcgan for the Synthesis of Multivariate Multifractal Textures: How do We Know it Works? by Mauduit, V., Abry, P., Leonarduzzi, R., Roux, S. G., Quemener, E.

    “…Deep Learning is nowadays widely used for several tasks in image processing. Notably, it has been massively used for image synthesis, mostly however with…”
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    Conference Proceeding
  4. 4

    Intrapartum fetal heart rate classification from trajectory in Sparse SVM feature space by Spilka, J., Frecon, J., Leonarduzzi, R., Pustelnik, N., Abry, P., Doret, M.

    “…Intrapartum fetal heart rate (FHR) constitutes a prominent source of information for the assessment of fetal reactions to stress events during delivery. Yet,…”
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    Conference Proceeding Journal Article
  5. 5

    P-leader multifractal analysis and sparse SVM for intrapartum fetal acidosis detection by Leonarduzzi, R., Spilka, J., Frecon, J., Wendt, H., Pustelnik, N., Jaffard, S., Abry, P., Doret, M.

    “…Interpretation and analysis of intrapartum fetal heart rate, enabling early detection of fetal acidosis, remains a challenging signal processing task. Among…”
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    Conference Proceeding Journal Article
  6. 6

    p-exponent and p-leaders, Part I: Negative pointwise regularity by Jaffard, S., Melot, C., Leonarduzzi, R., Wendt, H., Abry, P., Roux, S.G., Torres, M.E.

    Published in Physica A (15-04-2016)
    “…Multifractal analysis aims to characterize signals, functions, images or fields, via the fluctuations of their local regularity along time or space, hence…”
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    Journal Article
  7. 7

    p-exponent and p-leaders, Part II: Multifractal analysis. Relations to detrended fluctuation analysis by Leonarduzzi, R., Wendt, H., Abry, P., Jaffard, S., Melot, C., Roux, S.G., Torres, M.E.

    Published in Physica A (15-04-2016)
    “…Multifractal analysis studies signals, functions, images or fields via the fluctuations of their local regularity along time or space, which capture crucial…”
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    Journal Article
  8. 8

    Assessing Cross-Dependencies Using Bivariate Multifractal Analysis by Wendt, H., Leonarduzzi, R., Abry, P., Roux, S., Jaffard, S., Seuret, S.

    “…Multifractal analysis, notably with its recent wavelet-leader based formulation, has nowadays become a reference tool to characterize scale-free temporal…”
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    Conference Proceeding
  9. 9

    exponent and -leaders, Part II: Multifractal analysis. Relations to detrended fluctuation analysis by Leonarduzzi, R, Wendt, H, Abry, P, Jaffard, S, Melot, C, Roux, S G, Torres, ME

    Published in Physica A (15-04-2016)
    “…Multifractal analysis studies signals, functions, images or fields via the fluctuations of their local regularity along time or space, which capture crucial…”
    Get full text
    Journal Article
  10. 10

    exponent and -leaders, Part I: Negative pointwise regularity by Jaffard, S, Melot, C, Leonarduzzi, R, Wendt, H, Abry, P, Roux, S G, Torres, ME

    Published in Physica A (15-04-2016)
    “…Multifractal analysis aims to characterize signals, functions, images or fields, via the fluctuations of their local regularity along time or space, hence…”
    Get full text
    Journal Article
  11. 11

    P-leader multifractal analysis for text type identification by Leonarduzzi, R., Abry, P., Jaffard, S., Wendt, H., Gournay, L., Kyriacopoulou, T., Martineau, C., Martinez, C.

    “…Among many research efforts devoted to automated art investigations, the problem of quantification of literary style remains current. Meanwhile, linguists and…”
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    Conference Proceeding
  12. 12

    Multifractal Characterization for Bivariate Data by Leonarduzzi, R., Abry, P., Roux, S., Wendt, H., Jaffard, S., Seuret, S.

    “…Multifractal analysis is a reference tool for the analysis of data based on local regularity, which has been proven useful in an increasing number of…”
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    Conference Proceeding
  13. 13

    Scale-Free Functional Connectivity Analysis from Source Reconstructed MEG Data by Rocca, D. La, Ciuciu, P., van Wassenhove, V., Wendt, H., Abry, P., Leonarduzzi, R.

    “…Scale-free dynamics, quantified as power law spectra from magnetoencepholagraphic (MEG) recordings of Human brain activity, may play an important role in…”
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    Conference Proceeding
  14. 14