Author

Tamar Schwartz

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Systems Biology· 1

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1

Frequent Co-Authors

Assaf ZaritskyiD· 1 shared Daniel S. SeidmaniD· 1 shared Daniella Gilboa· 1 shared Marcos MesegueriD· 1 shared Maya Tsarfati ShapiroiD· 1 shared Oded RotemiD· 1 shared Ron Maor· 1 shared Yishay Tauber· 1 shared

Activity by Year

2024-2024 · peak 1/yr

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8 top collaborators · 28 mutual co-author links

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1 shared paperSystems Biology

Assaf ZaritskyORCID

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1 paper

Recent·Most cited

Visual interpretability of image-based classification models by generative latent space disentanglement applied to in vitro fertilization

Oded Rotem, Tamar Schwartz, Ron Maor, Yishay Tauber, Maya Tsarfati Shapiro, Marcos Meseguer, Daniella Gilboa, Daniel S. Seidman, Assaf Zaritsky

This paper introduces DISCOVER, a generative model that disentangles latent spaces to provide interpretable explanations for image-based classification models in in vitro fertilization.

Nature Communications · Aug 27, 2024Peer-reviewedSystems Biology