Learning an Efficient Texture Model by Supervised Nonlinear Dimensionality Reduction Methods. - Elnaz Barshan; Mina Behravan; Zohreh Azimifar (CIARP, 2009)

Supervised principal component analysis: Visualization, classification and regression on subspaces and submanifolds. - Elnaz Barshan; Ali Ghodsi 001; Zohreh Azimifar; Mansoor Zolghadri Jahromi (Pattern Recognit., 2011)

Scalable learning for restricted Boltzmann machines. - Elnaz Barshan; Paul W. Fieguth (ICIP, 2014)

Scalable multi-neighborhood learning for convolutional networks. - Elnaz Barshan; Paul W. Fieguth; Alexander Wong (MLSP, 2015)

Stage-wise Training: An Improved Feature Learning Strategy for Deep Models. - Elnaz Barshan; Paul W. Fieguth (FE@NIPS, 2015)

Learning Efficient Deep Feature Representations via Transgenerational Genetic Transmission of Environmental Information During Evolutionary Synthesis of Deep Neural Networks. - M. J. Shafiee; Elnaz Barshan; Francis Li; Brendan Chwyl; Michelle Karg; Christian Scharfenberger; Alexander Wong (ICCV Workshops, 2017)

Evolution in Groups: A deeper look at synaptic cluster driven evolution of deep neural networks. - Mohammad Javad Shafiee; Elnaz Barshan; Alexander Wong (CoRR, 2017)

Manifold Preserving Adversarial Learning. - Ousmane Amadou Dia; Elnaz Barshan; Reza Babanezhad 001 (CoRR, 2019)

RelatIF: Identifying Explanatory Training Samples via Relative Influence. - Elnaz Barshan; Marc-Etienne Brunet; Gintare Karolina Dziugaite (AISTATS, 2020)

RelatIF: Identifying Explanatory Training Examples via Relative Influence. - Elnaz Barshan; Marc-Etienne Brunet; Gintare Karolina Dziugaite (CoRR, 2020)

LECA: A learned approach for efficient cover-agnostic watermarking. - Xiyang Luo; Michael Goebel; Elnaz Barshan; Feng Yang (Media Watermarking, Security, and Forensics, 2023)