Publications

High-dimensional data modeling and analysis

  • B. Blancard, E. Allys, C. Auclair, F. Boulanger, M. Eickenberg, F. Levrier, L, Vacher, S. Zhang, Generative Models of Multichannel Data from a Single Example – Application to Dust Emission, The Astrophysical Journal, 2023 [url] [eprint] [pdf] [code]
  • A. Brochard, S. Zhang, S. Mallat, Generalized rectifier wavelet covariance models for texture synthesis, International Conference on Learning Representations, 2022 [url] [eprint] [pdf] [code]
  • A. Brochard, B. Blaszczyszyn, S. Zhang, S. Mallat, Particle gradient descent model for point process generation, Statistics and Computing, 2022 [url] [eprint] [pdf] [code]
  • S. Zhang, S. Mallat, Maximum entropy models from phase harmonic covariances, Applied and Computational Harmonic Analysis, 2021 [url] [eprint] [pdf] [code]
  • S. Mallat, S. Zhang, G. Rochette, Phase harmonic correlations and convolutional neural networks, Information and Inference: A Journal of the IMA, 2020 [url] [eprint] [pdf] [code]
  • E. Allys, F. Levrier, S. Zhang, C. Colling, B. Blancard, F. Boulanger, P. Hennebelle, S. Mallat, The RWST, a comprehensive statistical description of the non-Gaussian structures in the ISM, Astronomy & Astrophysics, 2019 [url] [eprint] [pdf]

Representation learning for recognition and inverse problems

  • P. Boudier, A. Fillion, S. Gratton, S. Gurol, S. Zhang, Data assimilation networks, Journal of Advances in Modeling Earth Systems, 2023 [url] [eprint] [pdf] [code]
  • S. Zhang, E. Soubies, C. Fevotte, Leveraging Joint-Diagonalization in Transform-Learning NMF, IEEE Transactions on Signal Processing, 2022 [url] [eprint] [pdf] [code]
  • S. Zhang, E. Soubies, C. Fevotte, On the identifiability of transform learning for non-negative matrix factorization, IEEE Signal Processing Letters, 2020 [url] [eprint] [pdf] [code]
  • M. Andreux, et al., Kymatio: Scattering transforms in python, Journal of Machine Learning Research, 2020 [url] [eprint] [pdf] [code]
  • A. Brochard, B. Blaszczyszyn, S. Mallat, S. Zhang, Statistical learning of geometric characteristics of wireless networks, IEEE Infocom, 2019 [url] [eprint] [pdf]
  • L. Wan, M. Zeiler, S. Zhang, Y. LeCun, R. Fergus, Regularization of Neural Networks using DropConnect, International Conference on Machine Learning, 2013 [url] [pdf]

Optimization algorithms

  • S. Zhang, On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes, Mathematical and Scientific Machine Learning, 2022 [url] [eprint] [pdf]
  • S. Zhang, A. Choromanska, Y. LeCun, Deep learning with Elastic Averaging SGD, Advances in Neural Information Processing Systems, 2015 [url] [eprint] [pdf] [code]
  • T. Schaul, S. Zhang, Y. LeCun, No more pesky learning rates, International Conference on Machine Learning, 2013 [url] [eprint] [pdf]
Thème : Overlay par Kaira. Texte supplémentaire
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