No more pesky learning rates. - Tom Schaul; Sixin Zhang; Yann LeCun (ICML (3), 2013)

Regularization of Neural Networks using DropConnect. - Li Wan 002; Matthew D. Zeiler; Sixin Zhang; Yann LeCun; Rob Fergus (ICML (3), 2013)

Deep learning with Elastic Averaging SGD. - Sixin Zhang; Anna Choromanska; Yann LeCun (ICLR (Workshop), 2015)

Distributed stochastic optimization for deep learning (thesis). - Sixin Zhang (CoRR, 2016)

Distributed Stochastic Optimization for Deep Learning. - Sixin Zhang (2016)

Phase Harmonics and Correlation Invariants in Convolutional Neural Networks. - Stéphane Mallat; Sixin Zhang; Gaspar Rochette (CoRR, 2018)

Kymatio: Scattering Transforms in Python. - Mathieu Andreux; Tomás Angles; Georgios Exarchakis; Roberto Leonarduzzi; Gaspar Rochette; Louis Thiry; John Zarka; Stéphane Mallat; Joakim Andén; Eugene Belilovsky; Joan Bruna; Vincent Lostanlen; et al. (CoRR, 2018)

Statistical learning of geometric characteristics of wireless networks. - Antoine Brochard; Bartlomiej Blaszczyszyn; Stéphane Mallat; Sixin Zhang (INFOCOM, 2019)

Maximum Entropy Models from Phase Harmonic Covariances. - Sixin Zhang; Stéphane Mallat (CoRR, 2019)

Kymatio: Scattering Transforms in Python. - Mathieu Andreux; Tomás Angles; Georgios Exarchakis; Roberto Leonarduzzi; Gaspar Rochette; Louis Thiry; John Zarka; Stéphane Mallat; Joakim Andén; Eugene Belilovsky; Joan Bruna; Vincent Lostanlen; et al. (J. Mach. Learn. Res., 2020)

On the Identifiability of Transform Learning for Non-Negative Matrix Factorization. - Sixin Zhang; Emmanuel Soubies; Cédric Févotte (IEEE Signal Process. Lett., 2020)

On the Relationships between Transform-Learning NMF and Joint-Diagonalization. - Sixin Zhang; Emmanuel Soubies; Cédric Févotte (CoRR, 2021)

Generalized rectifier wavelet covariance models for texture synthesis. - Antoine Brochard; Sixin Zhang; Stéphane Mallat (ICLR, 2022)

On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes. - Sixin Zhang (MSML, 2022)

Particle gradient descent model for point process generation. - Antoine Brochard; Bartlomiej Blaszczyszyn; Sixin Zhang; Stéphane Mallat (Stat. Comput., 2022)

Leveraging Joint-Diagonalization in Transform-Learning NMF. - Sixin Zhang; Emmanuel Soubies; Cédric Févotte (IEEE Trans. Signal Process., 2022)

Transform learning NMF. - Sixin Zhang (IEEE DataPort, 2022)

Combining Statistical Depth and Fermat Distance for Uncertainty Quantification. - Hai-Vy Nguyen; Fabrice Gamboa; Reda Chhaibi; Sixin Zhang; Serge Gratton; Thierry Giaccone (NeurIPS, 2024)

Local convergence of min-max algorithms to differentiable equilibrium on Riemannian manifold. - Sixin Zhang (CoRR, 2024)

Large Margin Discriminative Loss for Classification. - Hai-Vy Nguyen; Fabrice Gamboa; Sixin Zhang; Reda Chhaibi; Serge Gratton; Thierry Giaccone (CoRR, 2024)

CNN-based Compressor Mass Flow Estimator in Industrial Aircraft Vapor Cycle System. - Justin Reverdi; Sixin Zhang; Saïd Aoues; Fabrice Gamboa; Serge Gratton; Thomas Pellegrini (CoRR, 2024)

Local convergence of simultaneous min-max algorithms to differential equilibrium on Riemannian manifold. - Sixin Zhang (ICLR, 2025)

Convolutional Rectangular Attention Module. - Hai-Vy Nguyen; Fabrice Gamboa; Sixin Zhang; Reda Chhaibi; Serge Gratton; Thierry Giaccone (CoRR, 2025)

Feature Representation Transferring to Lightweight Models via Perception Coherence. - Hai-Vy Nguyen; Fabrice Gamboa; Sixin Zhang; Reda Chhaibi; Serge Gratton; Thierry Giaccone (CoRR, 2025)