Scholar

Orcid

Arxiv

Preprints

  1. Fort, G., Pascal, B., Abry, P., & Pustelnik, N. (2022). Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers.
  2. Lucas, C.-G., Pascal, B., Pustelnik, N., & Abry, P. (2021). Hyperparameters selection for the Discrete Mumford-Shah model.

Journal articles

  1. Pascal, B., & Bardenet, R. (2022). A covariant, discrete time-frequency representation tailored for zero-based signal detection. IEEE Transactions on Signal Processing, 70, 2950–2961.
  2. Pascal, B., Abry, P., Pustelnik, N., Roux, S., Gribonval, R., & Flandrin, P. (2022). Nonsmooth convex optimization to estimate the Covid-19 reproduction number space-time evolution with robustness against low quality data. IEEE Transactions on Signal Processing, 70, 2859–2868.
  3. Pascal, B., Pustelnik, N., & Abry, P. (2021). Strongly Convex Optimization for Joint Fractal Feature Estimation and Texture Segmentation. Applied and Computational Harmonic Analysis, 54, 303–322.
  4. Pascal, B., Vaiter, S., Pustelnik, N., & Abry, P. (2021). Automated data-driven selection of the hyperparameters for Total-Variation based texture segmentation. J. Math. Imaging Vis., 1–30.
  5. Pascal, B., Pustelnik, N., Abry, P., J.-C., G., & Vidal, V. Parameter-free and fast nonlinear piecewise filtering: application to experimental physics. Ann. Telecommun., 75(11), 655–671.

Conference papers

  1. Le, H. T. V., Pascal, B., Pustelnik, N., Foare, M., & Abry, P. (2022, September). Algorithmes proximaux rapides déroulés pour l’analyse d’images fractales homogènes par morceaux. GRETSI’22 XXVIIIème Colloque Francophone De Traitement Du Signal Et Des Images.
  2. Pascal, B., & Bardenet, R. (2022, September). Une famille de représentations covariantes de signaux discrets et son application ‘a la détection de signaux à partir de leurs zéros. GRETSI’22 XXVIIIème Colloque Francophone De Traitement Du Signal Et Des Images.
  3. Abry, P., Fort, G., Pascal, B., & Pustelnik, N. (2022, July). Temporal evolution of the Covid19 pandemic reproduction number: Estimations from proximal optimization to Monte Carlo sampling. 44th Annual International Conference of IEEE Eng. Med. Biol. Soc.
  4. Abry, P., Fort, G., Pascal, B., & Pustelnik, N. (2022, September). Estimation et intervalles de crédibilité pour le taux de reproduction de la Covid19 par échantillonnage Monte Carlo Langevin proximal. GRETSI’22 XXVIIIème Colloque Francophone De Traitement Du Signal Et Des Images.
  5. Artigas, H., Pascal, B., Fort, G., Abry, P., & Pustelnik, N. (2022, August). Credibility interval design for COVID19 reproduction number from nonsmooth Langevin-type Monte Carlo sampling. EUSIPCO 2022.
  6. Pascal, B., Mauduit, V., Abry, P., & Pustelnik, N. (2021, January). Scale-free Texture Segmentation: Expert Feature-based versus Deep Learning strategies. EUSIPCO 2020.
  7. Busser, T., Pascal, B., Pustelnik, N., Abry, P., Serres, M., Philippe, R., & Vidal, V. (2019). Ecoulement gaz-liquide dans un milieu poreux confiné: caractérisation par analyse d’images. Rencontres Du Non-Linéaire 2019.
  8. Pascal, B., Busser, T., Pustelnik, N., Abry, P., & Vidal, V. (2019). Segmentation d’images texturées en grande dimension. Application à l’analyse d’écoulements multiphasiques. GRETSI 2019 XXVIIème Colloque Francophone De Traitement Du Signal Et Des Images.
  9. Pascal, B., Pustelnik, N., Abry, P., Serres, M., & Vidal, V. (2018). Joint estimation of local variance and local regularity for texture segmentation. Application to multiphase flow characterization. Proc. Int. Conf. Image Process., 2092–2096.
  10. Pascal, B., Pustelnik, N., Abry, P., & Pesquet, J.-C. (2018). Block-coordinate proximal algorithms for scale-free texture segmentation. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1253–1257.

Thesis

  1. Pascal, B. (2020). Estimation régularisée d’attributs fractals par minimisation convexe pour la segmentation de textures [École Normale Supérieure de Lyon].