Y. F. Atchadé, G. Fort, and E. Moulines, On perturbed proximal gradient algorithms, J. Mach. Learn. Res, vol.18, issue.10, p.33, 2017.

J. Bruna and S. Mallat, Multiscale Sparse Microcanonical Models, 2018.
DOI : 10.4171/msl/7

URL : http://arxiv.org/pdf/1801.02013

D. Cano and T. Minh, Texture synthesis using hierarchical linear transforms, Signal Processing, vol.15, issue.2, pp.131-148, 1988.
DOI : 10.1016/0165-1684(88)90066-7

V. De-bortoli, A. Durmus, M. Pereyra, and A. Fernandez-vidal, Stochastic optimization with unadjusted kernel: the SOUK algorithm, 2019.
URL : https://hal.archives-ouvertes.fr/hal-01978999

J. Deng, W. Dong, R. Socher, L. Li, K. Li et al., Imagenet: A large-scale hierarchical image database, CVPR. pp, pp.248-255, 2009.

A. A. Efros and T. K. Leung, Texture synthesis by non-parametric sampling, ICCV. pp, pp.1033-1038, 1999.
DOI : 10.1109/iccv.1999.790383

URL : http://http.cs.berkeley.edu/projects/vision/papers/efros-iccv99.pdf

A. Gagalowicz and S. D. Ma, Model driven synthesis of natural textures for 3-d scenes, Computers & Graphics, vol.10, issue.2, pp.161-170, 1986.

B. Galerne, A. Leclaire, and J. Rabin, A texture synthesis model based on semidiscrete optimal transport in patch space, SIIMS, vol.11, issue.4, pp.2456-2493, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01726443

B. Galerne, Y. Gousseau, and J. Morel, Random phase textures: theory and synthesis, IEEE Trans. Image Processing, vol.20, issue.1, pp.257-267, 2011.
DOI : 10.1109/tip.2010.2052822

URL : https://hal.archives-ouvertes.fr/hal-00418389

L. A. Gatys, A. S. Ecker, and M. Bethge, Texture synthesis using convolutional neural networks. In: NIPS. pp, pp.262-270, 2015.

L. A. Gatys, A. S. Ecker, M. Bethge, A. Hertzmann, and E. Shechtman, Controlling perceptual factors in neural style transfer, CVPR. pp, pp.3730-3738, 2017.

A. Gretton, K. M. Borgwardt, M. J. Rasch, B. Schölkopf, and A. J. Smola, A kernel method for the two-sample-problem, NIPS. pp, pp.513-520, 2006.

D. J. Heeger and J. R. Bergen, Pyramid-based texture analysis/synthesis, ICIP. pp, pp.648-651, 1995.

E. T. Jaynes, Information theory and statistical mechanics, Phys. Rev, vol.106, pp.620-630, 1957.

N. Jetchev, U. Bergmann, and R. Vollgraf, Texture synthesis with spatial generative adversarial networks, 2016.

G. Liu, Y. Gousseau, and G. Xia, Texture synthesis through convolutional neural networks and spectrum constraints, pp.3234-3239, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01567165

Y. Lu, S. Zhu, and Y. N. Wu, Learning FRAME models using CNN filters, pp.1902-1910, 2016.

H. E. Ogden, A sequential reduction method for inference in generalized linear mixed models, Electron. J. Stat, vol.9, issue.1, pp.135-152, 2015.

G. Peyré, Texture synthesis with grouplets, IEEE Trans. Pattern Anal. Mach. Intell, vol.32, issue.4, pp.733-746, 2010.

J. Portilla and E. P. Simoncelli, A parametric texture model based on joint statistics of complex wavelet coefficients, IJCV, vol.40, issue.1, pp.49-70, 2000.

L. Raad, A. Davy, A. Desolneux, and J. Morel, A survey of exemplar-based texture synthesis, Annals of Mathematical Sciences and Applications, vol.3, pp.89-148, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01553841

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition, 2014.

D. Ulyanov, V. Lebedev, A. Vedaldi, and V. S. Lempitsky, Texture networks: Feedforward synthesis of textures and stylized images, pp.1349-1357, 2016.

I. Ustyuzhaninov, W. Brendel, L. A. Gatys, and M. Bethge, Texture synthesis using shallow convolutional networks with random filters, 2016.

J. J. Van-wijk, Spot noise texture synthesis for data visualization, SIGGRAPH. pp, pp.309-318, 1991.

S. C. Zhu, Y. N. Wu, and D. Mumford, Filters, random fields and maximum entropy (FRAME): towards a unified theory for texture modeling, IJCV, vol.27, issue.2, pp.107-126, 1998.