Sophie Achard, Marianne Clausel, Irène Gannaz, and François Roueff. New results on approximate hilbert pairs of wavelet filters with common factors. Applied and Computational Harmonic Analysis, 49(3):1025 – 1045, 2020. ISSN 1063-5203. [doi]. URL http://www.sciencedirect.com/science/article/pii/S1063520319301046.

   R. Alléaume, F. Roueff, O. Maurhart, and N. Lutkenhaus. Architecture, security and topology of a global quantum key distribution network. In 2006 Digest of the LEOS Summer Topical Meetings, pages 38–39. LEOS Summer Topical Meetings, 2006. [doi].

   R. Alléaume, F. Roueff, E. Diamanti, and N. Lütkenhaus. Qkd networks : topological optimization. New Journal of Physics, 11, 2009. [doi]. Focus on Quantum Cryptography.

   A. Ayache and F. Roueff. A Fourier formulation of the Frostman criterion for random graphs and its applications to wavelet series. Appl. Comput. Harmon. Anal., 14(1):75–82, 2003. ISSN 1063-5203. [doi].

   A. Ayache, F. Roueff, and Y. Xiao. Local and asymptotic properties of linear fractional stable sheets. C. R. Acad. Sci. Paris, Ser. I., 344(6):389–394, 2007a. [doi].

   A. Ayache, F. Roueff, and Y. Xiao. Joint continuity of the local times of linear fractional stable sheets. C. R. Acad. Sci. Paris, Ser. I., 344(10):635–640, 2007b. [doi].

   A. Ayache, F. Roueff, and Y. Xiao. Linear fractional stable sheets: wavelet expansion and sample path properties. Stoch. Proc. App., 119(4):1168–1197, 2009. [doi]. preprint available at [HAL] or [arXiv].

   B. Benmammar, C. Lévy-Leduc, and F. Roueff. Algorithme de détection d’attaques de type syn flooding. In Proc. of GRETSI, 2007. [pdf].

   B. Benmammar, C. Lévy-Leduc, and F. Roueff. Logiciel toprank. Déposé à l’APP (Agence pour la Protection des Programmes), 2008.

   P. Bianchi, J. Jakubowicz, and F. Roueff. Neyman-pearson detection of a gaussian source using dumb wireless sensors. In IEEE Statistical Signal Processing 2009, June 2009.

   P. Bianchi, J. Jakubowicz, and F. Roueff. Linear precoders for the detection of a gaussian process in wireless sensors networks. IEEE Transactions on Signal Processing, 59(3):882–894, March 2011. [doi]. preprint on [arXiv].

   C. Bordenave, Y. Gousseau, and F. Roueff. The dead leaves model : an example of a general tessellation. Advances in Applied Probability, 38(1):31–46, 2006. [doi].

   Dimitri Bouche, Marianne Clausel, François Roueff, and Florence d’Alché Buc. Nonlinear Functional Output Regression: a Dictionary Approach. working paper or preprint, January 2021. URL https://hal.archives-ouvertes.fr/hal-03122020.

   O. Cappé and F. Roueff. Evaluation numérique de l’information de fisher pour des observations irrégulières de l’état d’une file d’attente. In Proc. of GRETSI, 2003. [pdf].

   M. Clausel, F. Roueff, M. S. Taqqu, and C. Tudor. High order chaotic limits of wavelet scalograms under long–range dependence. ALEA Lat. Am. J. Probab. Math. Stat., 10(2): 979–1011, 2013. URL http://alea.impa.br/articles/v10/10-40.pdf.

   M. Clausel, F. Roueff, M. S. Taqqu, and C. Tudor. Wavelet estimation of the long memory parameter for Hermite polynomial of Gaussian processes. ESAIM P&S, 18:42–76, 2014a. [doi]. preprint available at [HAL] or [arXiv].

   M. Clausel, F. Roueff, M. S. Taqqu, and C. Tudor. Asymptotic behavior of the quadratic variation of the sum of two Hermite processes of consecutive orders. Stoch. Proc. App., 124(7):2517–2541, 2014b. [doi]. URL http://authors.elsevier.com/sd/article/S0304414914000519. Preprint available at [HAL] or [arXiv].

   Marianne Clausel, François Roueff, Murad S. Taqqu, and Ciprian Tudor. Large scale behavior of wavelet coefficients of non-linear subordinated processes with long memory. Applied and Computational Harmonic Analysis, 32(2):223–241, 2012. ISSN 1063-5203. [doi]. URL http://www.sciencedirect.com/science/article/pii/S1063520311000601. preprint available at [HAL] or [arXiv].

   Marianne Clausel, François Roueff, and Murad S. Taqqu. Large scale reduction principle and application to hypothesis testing. Electron. J. Statist., 9(2):153–203, 2015. [doi]. URL http://projecteuclid.org/euclid.ejs/1423229754. preprint available at [HAL] or [arXiv].

   Kamélia Daudel and François Roueff. Learning with Importance Weighted Variational Inference: Asymptotics for Gradient Estimators of the VR-IWAE Bound. working paper or preprint, October 2024. URL https://hal.science/hal-04738844.

   Kamélia Daudel. Adaptative Monte-Carlo methods for complex models. PhD thesis, EDMH, 2021. URL http://www.theses.fr/2021IPPAT024. Thèse de doctorat dirigée par Roueff, François et Douc, Randal Mathématiques appl iquées Institut polytechnique de Paris 2021.

   Kamélia Daudel, Randal Douc, and François Roueff. Monotonic alpha-divergence minimisation for variational inference. Journal of Machine Learning Research, 24(62):1–76, 2023. URL http://jmlr.org/papers/v24/21-0249.html.

   Marine Depecker. Statistical learning methods for bipartite ranking. Theses, Télécom ParisTech, December 2010. URL https://pastel.archives-ouvertes.fr/pastel-00572421.

   R. Douc, F. Roueff, and P. Soulier. On the existence of some ARCH(∞) processes. Stoch. Proc. App., 118(5):755–761, 2007. [doi]. preprint available at [arXiv].

   Randal Douc, François Roueff, and Tepmony Sim. Handy sufficient conditions for the convergence of the maximum likelihood estimator in observation-driven models. Lithuanian Mathematical Journal, 55(3):367–392, July 2015. [doi]. URL http://link.springer.com/article/10.1007/s10986-015-9286-8. Preprint available at [HAL] or [arXiv].

   Randal Douc, François Roueff, and Tepmony Sim. The maximizing set of the asymptotic normalized log-likelihood for partially observed markov chains. Ann. Appl. Probab., 26(4): 2357–2383, 2016. ISSN 1050-5164. [doi]. Preprint available at [HAL] or [arXiv].

   Randal Douc, Jimmy Olsson, and François Roueff. Posterior consistency for partially observed Markov models. Stochastic Processes and their Applications, 130(2):733–759, February 2020. [doi]. URL https://hal.science/hal-04081621.

   Randal Douc, François Roueff, and Tepmony Sim. Necessary and sufficient conditions for the identifiability of observation-driven models. Journal of Time Series Analysis, 42(2):140–160, 2021. [doi]. URL https://onlinelibrary.wiley.com/doi/abs/10.1111/jtsa.12559.

   Paul Doukhan, François Roueff, and Joseph Rynkiewicz. Spectral estimation for non-linear long range dependent discrete time trawl processes. Electron. J. Statist., 14(2):3157–3191, 2020. ISSN 1935-7524. [doi].

   Amaury Durand. Functional time series modeling and application to representation and analysis of multi-site electric load curves for energy management. PhD thesis, EDMH, 2022. URL http://www.theses.fr/2022IPPAT018. Thèse de doctorat dirigée par Roueff, François Mathématiques appliquées Institut polytechnique de Paris 2022.

   Amaury Durand and François Roueff. Hilbert space-valued fractionally integrated autoregressive moving average processes with long memory operators. Journal of Statistical Planning and Inference, 231:106146, 2024. ISSN 0378-3758. [doi]. URL https://www.sciencedirect.com/science/article/pii/S037837582400003X.

   Amaury Durand, François Roueff, Jean-Marc Jicquel, and Nicolas Paul. Smooth nonnegative tensor factorization for multi-sites electrical load monitoring. In EUSIPCO, Dublin, Ireland, August 2021. URL https://hal.telecom-paris.fr/hal-03167498.

   Amaury Durand, François Roueff, Jean-Marc Jicquel, and Nicolas Paul. New penalized criteria for smooth non-negative tensor factorization with missing entries. IEEE Transactions on Signal Processing, 72:2233–2243, 2024. [doi].

   Durand, Amaury and Roueff, François. Weakly stationary stochastic processes valued in a separable hilbert space: Gramian-cramér representations and applications. ESAIM: PS, 27: 776–809, 2023. [doi]. URL https://doi.org/10.1051/ps/2023014.

   Anton Emelchenkov, Mathieu Fontaine, Yves Grenier, Hervé Mahé, and François Roueff. Multifrequency Highly Oscillating Aperiodic Amplitude Estimation for Nonlinear Chirp Signal. In European Signal Processing Conference (EUSIPCO), Lyon, France, August 2024. URL https://hal.science/hal-04614241.

   G. Fay, F. Roueff, and P. Soulier. Estimation of the memory parameter of transmission rate measurements using an infinite source poisson model. In ASMDA2005, Brest, France, June 2005.

   G. Faý, F. Roueff, and P. Soulier. Estimation of the memory parameter of the infinite source Poisson process. Bernoulli, 13(2):473–491, 2007. [doi]. available at [arXiv].

   G. Faý, E. Moulines, F. Roueff, and M.S. Taqqu. Estimators of long-memory: Fourier versus wavelets. J. of Econometrics, 151(2):159–177, 2009. [doi]. preprint available at [HAL] or [arXiv].

   Jean-Francois Germain. Sélection de modèles à l’aide des chemins de régularisation pour l’objectivation mono et multi-prestations. Application à l’agrément de conduite. Theses, Télécom ParisTech, October 2008. URL https://pastel.archives-ouvertes.fr/pastel-00005150.

   Jean-Francois Germain and Francois Roueff. Weak convergence of the regularization path in penalized M-estimation. Scand. J. Stat., 37(3):477–495, 2010. ISSN 0303-6898. [doi]. preprint available at [HAL] or [arXiv].

   C. Giraud, F. Roueff, and A. Sánchez-Pérez. Adaptive online forecasting of a locally stationary time varying autoregressive process. In Statistical Inference for Complex Time Series Data, number 48 in Mathematisches Forschungsinstitut Oberwolfach, pages 53–56, 2013. [doi]. Available at MFO.

   Christophe Giraud, François Roueff, and Andres Sanchez-Perez. Aggregation of predictors for non stationary sub-linear processes and online adaptive forecasting of time varying autoregressive processes. Ann. Statist., 43(6):2412–2450, 2015. [doi]. URL http://projecteuclid.org/euclid.aos/1444222080. Preprint available at [HAL] or [arXiv].

   Y. Gousseau and F. Roueff. A geometrical a priori for capturing the regularity of images. In EUSIPCO 2005, 2005. [pdf].

   Y. Gousseau and F. Roueff. Modeling occlusion and scaling in natural images. SIAM Multiscale Modeling and Simulation, 6(1):105–134, 2007. [doi].

   W. Hachem, E. Moulines, J. Najim, and F. Roueff. On the error exponents for detecting randomly sampled noisy diffusion processes. In ICASSP, Taipei, Taiwan, April 2009. [pdf].

   W. Hachem, E. Moulines, and F. Roueff. Error exponents for Neyman-Pearson detection of a continuous-time Gaussian Markov process from regular or irregular samples. IEEE trans. on Information Theory, 57(6):3899–3914, June 2011. [doi].

   Paul Ilhe. Estimation statistique des éléments d’un processus shot-noise. PhD thesis, Télécom ParisTech, Sep 2016.

   Paul Ilhe, Éric Moulines, Francois Roueff, and Antoine Souloumiac. Nonparametric estimation of mark’s distribution of an exponential shot-noise process. Electron. J. Statist., 9 (2):3098–3123, 2015. [doi]. URL http://dx.doi.org/10.1214/15-EJS1103.

   O. Kouamo, E. Moulines, and F. Roueff. Testing for homogeneity of variance in the wavelet domain. In Paul Doukhan, Gabriel Lang, Donatas Surgailis, and Gilles Teyssière, editors, Dependence in probability and statistics, pages 175–205. Springer, Berlin, 2010. preprint available at [HAL].

   Olaf Kouamo. Long memory times series analysis usint wavelet domain. Theses, Télécom ParisTech, January 2011. URL https://pastel.archives-ouvertes.fr/pastel-00565656.

   Romain Laby. Anomaly Detection and Localisation Using Mixed Graphical Models. PhD thesis, Télécom ParisTech, May 2017.

   G. Lang and F. Roueff. Semi-parametric estimation of the Hölder exponent of a stationary Gaussian process with minimax rates. Statistical Inference for Stochastic Processes, 4:283–306, 2001. [doi].

   C. Lévy-Leduc and F. Roueff. Detection and localization of change-points in high-dimensional network traffic data. Annals Of Applied Statistics, 3(2):637–662, 2009. [doi]. available at [arXiv].

   C. Lévy-Leduc, E. Moulines, and F. Roueff. Frequency estimation based on the cumulated Lomb-Scargle periodogram. J. Time Ser. Anal., 29(6):1104–1131, 2008. ISSN 0143-9782. [doi]. preprint available at [HAL] or [arXiv].

   A. Lung-Yut-Fong, O. Cappé, C. Lévy-Leduc, and F. Roueff. Détection et localisation décentralisées d’anomalies dans le trafic internet. In GRETSI, Dijon, France, September 2009.

   E. Moulines, P. Priouret, and F. Roueff. Estimation récursive pour les modèles autorégressifs localement stationnaires. In GRETSI 2003, volume 1, pages 161–164, Paris, September 2003.

   E. Moulines, F. Roueff, and P. Priouret. Recursive estimation of a locally stationary process. In IEEE workshop on statistical signal processing, pages 110 – 113, 2003. [abs].

   E. Moulines, P. Priouret, and F. Roueff. On recursive estimation for time varying autoregressive processes. Ann. Statist., 33(6):2610–2654, 2005. ISSN 0090-5364. [doi]. available at [arXiv].

   E. Moulines, F. Roueff, A. Souloumiac, and T. Trigano. Nonparametric inference of photon energy distribution from indirect measurements. Bernoulli, 13(2):365–388, 2007a. [doi]. preprint available at [HAL] or [arXiv].

   E. Moulines, F. Roueff, and M.S. Taqqu. On the spectral density of the wavelet coefficients of long memory time series with application to the log-regression estimation of the memory parameter. J. Time Ser. Anal., 28(2):155–187, 2007b. [doi]. preprint available at [HAL] or [arXiv].

   E. Moulines, F. Roueff, and M.S. Taqqu. Central Limit Theorem for the log-regression wavelet estimation of the memory parameter in the Gaussian semi-parametric context. Fractals, 15(4):301–313, 2007c. [doi].

   E. Moulines, F. Roueff, and M.S. Taqqu. A wavelet Whittle estimator of the memory parameter of a non-stationary Gaussian time series. Ann. Statist., 36(4):1925–1956, 2008. [doi]. available at [arXiv].

   Tahar Nabil. Identification de modèle de bâtiment dans un environnement d’objets connectés. PhD thesis, Telecom ParisTech, January 2018.

   Tahar Nabil, Jean-Marc Jicquel, Alexandre Girard, and François Roueff. Système et procédé d’estimation du comportement thermique d’un bâtiment, pour un contrôle optimal de chauffage, August 2016. URL https://hal.science/hal-04200228.

   Tahar Nabil, Jean-Marc Jicquel, Alexandre Girard, and François Roueff. Procédé et dispositif de détermination indirecte d’un flux solaire incident, September 2017. URL https://hal.science/hal-04200222.

   Tahar Nabil, Jean-Marc Jicquel, Alexandre Girard, and François Roueff. Estimation d’un circuit électrique équivalent, à résistances et capacités thermiques, d’un bâtiment pour le contrôle optimal du chauffage du bâtiment, January 2018. URL https://hal.science/hal-04200219.

   A. Nouvellet. Avancées récentes en traitement statistique du signal appliquées à l’estimation et la détection d’ondes infrasonores. PhD thesis, TELECOM ParisTech, March 2017.

   Adrien Nouvellet, Maurice Charbit, François Roueff, and Alexis Le Pichon. Slowness estimation from noisy time delays observed on non-planar arrays. Geophys. J. Int., 198(2): 1199–1207, August 2014. [doi].

   Adrien Nouvellet, François Roueff, Alexis Le Pichon, Maurice Charbit, Julien Vergoz, Mohamed Kallel, and Chourouq Mejri. Local propagation speed constrained estimation of the slowness vector from non-planar array observations. J Acoust Soc Am., 139(1):559–567, January 2016. [doi].

   B Poste, M Charbit, A Le Pichon, C Listowski, F Roueff, and J Vergoz. The Multi-Channel Maximum-Likelihood (MCML) method: a new approach for infrasound detection and wave parameter estimation. Geophysical Journal International, 09 2022. ISSN 0956-540X. [doi]. URL https://doi.org/10.1093/gji/ggac377. ggac377.

   T. Rebafka, F. Roueff, and A. Souloumiac. Désempilement de mesures de temps de réponse par un algorithme e.m. modifié. In GRETSI 2009, Dijon, September 2009.

   T. Rebafka, F. Roueff, and A. Souloumiac. Procede d’estimation des parametres de la distribution des temps de reponse de particules d’un systeme, applique notamment aux mesures de fluorescence, August 2010.

   T. Rebafka, F. Roueff, and A. Souloumiac. A corrected likelihood approach for the nonlinear transformation model with application to fluorescence lifetime measurements using exponential mixtures. International Journal of Biostatistics, 6(1), 2010. [doi]. preprint available at [HAL].

   Tabea Rebafka. Estimation dans le modèle d’empilement avec application aux mesures de la fluorescence résolue en temps. Theses, Télécom ParisTech, October 2009. URL https://pastel.archives-ouvertes.fr/pastel-00005715.

   Tabea Rebafka and François Roueff. Nonparametric estimation of the mixing density using polynomials. Mathematical Methods of Statistics, 24(3):200–224, July 2015. [doi]. URL http://link.springer.com/article/10.3103/S1066530715030023. Preprint available at [HAL] or [arXiv].

   Tabea Rebafka, François Roueff, and Antoine Souloumiac. Information bounds and MCMC parameter estimation for the pile-up model. J. Statist. Plann. Inference, 141(1):1–16, 2011. ISSN 0378-3758. [doi]. preprint available at [HAL].

   F. Roueff. Dimension de Hausdorff du graphe d’une fonction continue: une étude analytique et statistique. PhD thesis, Ecole Nationale Supérieure des Télécommunications, 2000. [abs].

   F. Roueff. Dimension de Hausdorff du graphe d’une fonction continue: nouvelles majorations déterministes et minorations presque sûres. C. R. Acad. Sci. Paris Sér. I Math., 332(10): 875–880, 2001. ISSN 0764-4442. [doi].

   F. Roueff. Almost sure Hausdorff dimensions of graphs of random wavelet series. Journal of Fourier Analysis and Applications, 9(3):237–260, aug 2003a. [doi].

   F. Roueff. New upper bounds of the Hausdorff dimensions of graphs of continuous functions. Math. Proc. of the Cambridge Phil. Society, 135(2):219–237, sep 2003b. [doi].

   F. Roueff. Modélisation et estimation de la dépendance et de la régularité. Synthèse des travaux de recherche en vue de l’obtention du diplôme d’habilitation à diriger des recherches. Technical report, Université Paris X – Nanterre, 2007. [pdf] [abs].

   F. Roueff. Nonstationary models with long memory. In International Statistical Institute (58th congress), Dublin, Irelande, August 2011.

   F. Roueff and J. Lévy Véhel. A regularization approach to fractional dimension estimation. In Proc. of Fractals 98, Malta, 1998. [ps.gz].

   F. Roueff and T. Rydén. Nonparametric estimation of mixing densities for discrete distributions. Ann. Statist., 33(5):2066–2108, 2005. ISSN 0090-5364. [doi]. available at [arXiv].

   F. Roueff and A. Sánchez-Pérez. Numerical cost for time series prediction via aggregation. In Colloque Gretsi, Brest, France, September 2013.

   F. Roueff and P. Soulier. Convergence to stable laws in the space d. Journal of Applied Probability, 52(1): 1–17, 2015. [doi]. URL https://projecteuclid.org/euclid.jap/1429282603. Preprint available at [HAL],[arXiv].

   F. Roueff and M. S. Taqqu. Central limit theorems for arrays of decimated linear processes. Stoch. Proc. App., 119(9):3006–3041, 2009a. [doi]. preprint available at [HAL] or [arXiv].

   F. Roueff and M. S. Taqqu. Asymptotic normality of wavelet estimators of the memory parameter for linear processes. J. Time Ser. Anal., 30(5):534–558, 2009b. [doi]. preprint available at [HAL] or [arXiv].

   F. Roueff and R. von Sachs. Locally stationary long memory estimation. Stoch. Proc. App., 121(4):813 – 844, 2011. ISSN 0304-4149. [doi]. preprint available at [HAL].

   F. Roueff, G. Samorodnitsky, and P. Soulier. Function-indexed empirical processes based on an infinite source poisson transmission stream. Bernoulli, 18(3):783–802, August 2012. [HAL],[arXiv].

   François Roueff and Rainer von Sachs. Time-frequency analysis of locally stationary hawkes processes. Bernoulli, 25(2):1355–1385, 2019. ISSN 1350-7265. [doi]. preprint available at [HAL].

   François Roueff and Andrés Sánchez-Pérez. Prediction of weakly locally stationary processes by auto-regression. ALEA : Latin American Journal of Probability and Mathematical Statistics, 15:1215–1239, 2018. [doi]. preprint available at [HAL].

    François Roueff, Rainer von Sachs, and Laure Sansonnet. Locally stationary hawkes processes. Stochastic Processes and their Applications, 126(6):1710 – 1743, 2016. ISSN 0304-4149. [doi]. URL http://www.sciencedirect.com/science/article/pii/S0304414915003075.

   Andrés Sànchez Pérez. Aggregation of time series predictors, optimality in a locally stationary context. Theses, Télécom ParisTech, September 2015. URL https://pastel.archives-ouvertes.fr/tel-01280365.

   Tepmony Sim. Maximum likelihood estimation in partially observed Markov models with applications to time series of counts. Theses, Télécom ParisTech, March 2016. URL https://pastel.archives-ouvertes.fr/tel-01458087.

   Tepmony Sim, Randal Douc, and François Roueff. General-order observation-driven models: Ergodicity and consistency of the maximum likelihood estimator. Electron. J. Statist., 15(1): 3349–3393, 2021. ISSN 1935-7524. [doi].

   T. Trigano, A. Souloumiac, F. Roueff, and E. Moulines. Nonparametric Inference for Pileup Correction in Nuclear Spectroscopy. In IEEE Workshop on Statistical Signal Processing, Bordeaux, France, July 2005.

   T. Trigano, F. Roueff, E. Moulines, A. Souloumiac, and T. Montagu. Energy spectrum reconstruction for hpge detectors using analytical pile-up correction. In ICASSP, volume 3, 2006. [doi].

   T. Trigano, T. Montagu, E. Moulines, F. Roueff, and A. Souloumiac. Statistical pileup correction method for HPGe detectors. IEEE Trans. Signal Process., 55(10):4871–4881, 2007. [doi].

   Thomas Trigano. Traitement statistique du signal spectrometrique : Etude du désempilement de spectre en énergie pour la spectrométrie gamma. Theses, Télécom ParisTech, December 2005. URL https://pastel.archives-ouvertes.fr/tel-00080359.

   T. Wohlfarth, S. Clémençon, F. Roueff, and X. Casellato. Prédiction de l’occurence d’une baisse de prix pour le conseil à l’achat d’un billet en ligne. In GRETSI, BORDEAUX FRANCE, September 2011a.

   T. Wohlfarth, S. Clémençon, F. Roueff, and X. Casellato. A data-mining approach to travel price forecasting. In ICMLA, Honolulu (Hawaï), USA, December 2011b.

   Till Wohlfarth. A data-mining approach to travel price forecasting. Theses, Télécom ParisTech, December 2013. URL https://pastel.archives-ouvertes.fr/tel-01310537.

   Ban Zheng, François Roueff, and Frédéric Abergel. Modelling bid and ask prices using constrained Hawkes processes: Ergodicity and scaling limit. SIAM J. Finan. Math., 5(1): 99–136, February 2014. [doi]. Preprint available at [HAL] or [arXiv].