Preprints, accessible on arXiv
[33] J. Fageot, On Tempered Discrete and Lévy White Noises, arXiv preprint arXiv:2201.00797, 2022. [pdf]
[32] A. Caponera, J. Fageot, M. Simeoni, V. Panaretos, Nonparametric Estimation of Covariance and Autocovariance Operators on the Sphere, arXiv preprint arXiv:2112.12694, 2021. [pdf]
[31] A. Jarret, J. Fageot, M. Simeoni, A Fast and Scalable Polyatomic Frank-Wolfe Algorithm for the LASSO, arXiv preprint arXiv:2112.02890, 2021. [pdf]
[30] J. Fageot, J.P. Ward, The Critical Smoothness of Generalized Functions, arXiv preprint arXiv:2009.12491, 2020. [pdf]
[29] J. Fageot, T. Debarre, Q. Denoyelle, On the Uniqueness of Inverse Problems with Fourier-domain Measurements and Generalized TV Regularization, arXiv preprint arXiv:2009.11855, 2020. [pdf]
[28] J. Fageot, A. Fallah, T. Horel, Entropic Compressibility of Lévy Processes, arXiv preprint arXiv:2009.10753, 2020. [pdf]
[27] V. Oreiller, V. Andrearczyk, J. Fageot, J.O. Prior, A. Depeursinge, 3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis, arXiv preprint arXiv:2004.13371, 2020. [pdf]
[26] M. Unser, J. Fageot, Native Banach Spaces for Splines and Variational Inverse Problems, arXiv preprint arXiv:1904.10818, 2019. [pdf]
Publications
[25] T. Debarre, Q. Denoyelle, M. Unser, J. Fageot, Sparsest Piecewise-Linear Regression of One-Dimensional Data, Journal of Computational and Applied Mathematics, vol. 406, p.114044, 2022. [pdf]
[24] S. Aziznejad, J. Fageot, Wavelet Compressibility of Compound Poisson Processes, IEEE Transactions on Information Theory, in press, 2021. [pdf]
[23] J. Fageot, V. Uhlmann, Zs. Püspöki, B. Beck, M. Unser, A. Depeursinge, Principled Design and Implementation of Steerable Detectors, IEEE Transactions on Image Processing, vol. 30, pp. 4465-4478, 2021. [pdf]
[22] J. Fageot, T. Humeau, The Domain of Definition of Lévy White Noise, Stochastic Processes and their Applications, vol. 135, pp. 75-102, 2021. [pdf]
[21] S. Aziznejad, J. Fageot, Wavelet Analysis of the Besov Regularity of Lévy White Noises, Electronic Journal of Probability, vol. 25, paper no. 158, pp. 1-38, 2020. [pdf]
[20] J. Fageot, M. Simeoni, TV-based Reconstruction of Periodic Functions, Inverse Problems, vol. 36, no. 11, p. 115015, 2020. [pdf]
[19] V. Andrearczyk, J. Fageot, V. Oreiller, X. Montet, A. Depeursinge, Local Rotation Invariance in 3D CNNs, Medical Image Analysis, vol. 65, p. 101756, 2020. [pdf]
[18] A. Song, V. Uhlmann, J. Fageot, M. Unser, Sparse Dictionary Learning for Two-Dimensional Kendall Shapes, SIAM Journal of Imaging Science, vol. 13, no. 1, pp. 141-175, 2020. [pdf]
[17] J. Fageot, S. Aziznejad, M. Unser, V. Uhlmann, Support and Approximation Properties of Hermite Splines, Journal of Computational and Applied Mathematics, vol. 368, p. 112503, 2020. [pdf]
[16] J. Fageot, V. Uhlmann, M. Unser, Gaussian and Sparse Processes are Limits of Generalized Poisson Processes, Applied and Computational Harmonic Analysis, vol. 48, no. 3, pp. 1045-1065, 2020. [pdf]
[15] J. Fageot, M. Unser, Scaling Limits of Solutions of linear SDE Driven by Lévy White Noises, Journal of Theoretical Probability, vol. 32, no.3, pp. 1166-1189, 2019. [pdf]
[14] J. Fageot, M. Unser, J.P. Ward, Beyond Wiener’s Lemma: Nuclear Convolution Algebras and the Inversion of Digital Filters, Journal of Fourier Analysis and Applications, vol. 25, no.4, pp. 2037-2063, 2019. [pdf]
[13] J. Fageot, M. Unser, J.P. Ward, The n-term Approximation of Periodic Generalized Lévy Processes, Journal of Theoretical Probability, vol. 33, pp. 180-200, 2019. [pdf]
[12] T. Debarre, J. Fageot, H. Gupta, M. Unser, B-Spline-Based Exact Discretization of Continuous-Domain Inverse Problems with Generalized TV Regularization, IEEE Transactions on Information Theory, vol. 65, no. 7, pp. 4457-4470, 2019. [pdf]
[11] Zs. Püspöki, J. Fageot, A. Amini, J.P. Ward, M. Unser, Angular Accuracy of Steerable Feature Detectors, SIAM Journal on Imaging Sciences, vol. 12, no. 1, pp. 344-371, 2019. [pdf]
[10] A. Badoual, J. Fageot, M. Unser, Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems, IEEE Transactions on Signal Processing, vol. 66, no. 22, pp. 6047-6061, 2018. [pdf]
[9] H. Gupta, J. Fageot, M. Unser, Continuous-Domain Solutions of Linear Inverse Problems with Tikhonov vs. Generalized TV Regularization, IEEE Transactions on Information Theory, vol. 66, no. 17, pp. 4670-4684, 2018. [pdf]
[8] M. Unser, J. Fageot, J.P. Ward, Splines are Universal Solutions of Linear Inverse Problems with Generalized-TV Regularization, SIAM Review, vol. 59, no. 4, pp. 769-793, 2017. [pdf]
[7] D. Schmitter, J. Fageot, A. Badoual, P. Garcia-Amorena, M. Unser, Compactly-Supported Smooth Interpolators for Shape Modeling with Varying Resolution, Graphical Models, vol. 94, pp. 52-64, 2017. [pdf]
[6] J. Fageot, A. Fallah, M. Unser, Multidimensional Lévy White Noise in Weighted Besov Spaces, Stochastic Processes and their Applications, vol. 127, no. 5, pp. 1599-1621, 2017. [pdf]
[5] J. Fageot, M. Unser, J.P. Ward, On the Besov Regularity of Periodic Lévy Noises, Applied and Computational Harmonic Analysis, vol. 42, no. 1, pp. 21-36, 2017. [pdf]
[4] M. Unser, J. Fageot, H. Gupta, Representer Theorems for Sparsity-Promoting L1-Regularization, IEEE Transactions on Information Theory, vol. 62, no. 9, pp. 5167-5180, 2016. [pdf]
[3] V. Uhlmann, J. Fageot, M. Unser, Hermite Snakes with Control of Tangents, IEEE Transactions on Image Processing, vol. 25, no. 6, pp. 2803-2816, 2016. [pdf]
[2] J. Fageot, E. Bostan, M. Unser, Wavelet Statistics of Sparse and Self-similar Images, SIAM Journal on Imaging Sciences, vol. 8, no. 4, pp. 2951-2975, 2015. [pdf]
[1] J. Fageot, A. Amini, M. Unser, On the Continuity of the Characteristic Functionals and Sparse Stochastic Modeling, Journal of Fourier Analysis and Applications, vol. 20, no. 6, pp. 1179-1211, 2014. [pdf]
Book Chapters
[2] A. Depeursinge, J. Fageot, O.S. Al-Kadi, Fundamentals of Texture Processing for Biomedical Image Analysis, Biomedical Texture Analysis, A. Depeursinge, O.S. Al-Kadi, J.R. Mitchell, Eds., Academic Press, Ch. 1, pp. 7-36, 2017.
[1] A. Depeursinge, J. Fageot, Biomedical Texture Operators and Aggregation Functions, Biomedical Texture Analysis, A. Depeursinge, O.S. Al-Kadi, J.R. Mitchell, Eds., Academic Press, Ch. 3, pp. 63-100, 2017.
Conference Proceedings
[10] V. Oreiller, J. Fageot, V. Andrearczyk, J.O. Prior, A. Depeursinge, Multi-Organ Nucleus Segmentation Using a Locally Rotation Invariant Bispectrum U-Net, OpenReview (submitted to MIDL'22), 2022. [pdf]
[9] V. Andrearczyk, V. Oreiller, J. Fageot, X. Montet, A. Depeursinge, Solid Spherical Energy (SSE) CNNs for Efficient 3D Medical Image Analysis
, Medical Imaging with Deep Learning (MIDL'19), London, UK, July 2019. [pdf]
[8] V. Andrearczyk, J. Fageot, V. Oreiller, X. Montet, A. Depeursinge, Exploring Local Rotation Invariance in 3D CNNs with Steerable Filters, Medical Imaging with Deep Learning (MIDL'19), London, UK, July 2019. [pdf]
[7] T. Debarre, J. Fageot, H. Gupta, M. Unser, Solving Continuous-domain Problems Exactly with Multiresolution B-splines, ICASSP'19), Brighton, UK, May, 2019, pp. 5122-5126. [pdf]
[6] A. Depeursinge, J. Fageot, V. Andrearczyk, J.P. Ward, M. Unser, Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features, International Workshop on Machine Learning in Medical Imaging, Granada, Spain, September, 2018, pp. 107-115. [pdf]
[5] J. Fageot, J.P. Ward, M. Unser, Interpretation of Continuous-time Autoregressive Processes as Random Exponential Splines, Sampling Theory and Applications (SampTA'15), Washington DC, USA, May, 2015, pp. 231-235. [pdf]
[4] J.P. Ward, J. Fageot, M. Unser, Compressibility of Symmetric-alpha-stable Processes, Sampling Theory and Applications (SampTA'15), Washington DC, USA, May, 2015, pp. 236-240. [pdf]
[3] V. Uhlmann, J. Fageot, M. Unser, Statistical Optimality of Hermite Splines, Sampling Theory and Applications (SampTA'15), Washington DC, USA, May, 2015, pp. 226-230. [pdf]
[2] J. Fageot, E. Bostan, M. Unser, Statistics of Wavelet Coefficients for Sparse Self-similar Images, International Conference on Image Processing (ICIP'2014), Paris, France, October, 2014, pp. 6096-6100. [pdf]
[1] E. Bostan, J. Fageot, U.S. Kamilov, M. Unser, MAP Estimators for Self-similar Sparse Stochastic Processes, Sampling Theory and Applications (SampTA'13), Bremen, Germany, July, 2013, pp. 197-199. [pdf]
PhD Thesis
J. Fageot, Gaussian versus Sparse Stochastic Processes: Construction, Regularity, Compressibiilty, PhD Thesis, Swiss Federal Institute of Technology Lausanne (EPFL), under the supervision of Prof. M. Unser, 2017. [pdf]