Defending against Adversarial Images using Basis Functions Transformations. - Uri Shaham 001; James Garritano; Yutaro Yamada; Ethan Weinberger; Alex Cloninger; Xiuyuan Cheng; Kelly P. Stanton; Yuval Kluger (CoRR, 2018)

Learned Feature Attribution Priors. - Ethan Weinberger; Joseph D. Janizek; Su-In Lee (CoRR, 2019)

Learning Deep Attribution Priors Based On Prior Knowledge. - Ethan Weinberger; Joseph D. Janizek; Su-In Lee (NeurIPS, 2020)

Moment Matching Deep Contrastive Latent Variable Models. - Ethan Weinberger; Nicasia Beebe-Wang; Su-In Lee (AISTATS, 2022)

Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI. - Ethan Weinberger; Romain Lopez; Jan-Christian Hütter; Aviv Regev (MLCB, 2022)

Feature Selection in the Contrastive Analysis Setting. - Ethan Weinberger; Ian Covert; Su-In Lee (NeurIPS, 2023)

Modeling variable guide efficiency in pooled CRISPR screens with ContrastiveVI+. - Ethan Weinberger; Ryan Conrad; Tal Ashuach (CoRR, 2024)

CellCLIP - Learning Perturbation Effects in Cell Painting via Text-Guided Contrastive Learning. - Mingyu Lu; Ethan Weinberger; Chanwoo Kim; Su-In Lee (CoRR, 2025)