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Ethan Weinberger

5 accepted papers

2026

PETRI: Learning Unified Cell Embeddings from Unpaired Modalities via Early-Fusion Joint Reconstruction

ICLR 2026poster

Integrating multimodal screening data is challenging because biological signals only partially overlap and cell-level pairing is frequently unavailable. Existing approaches either require pairing or fail to capture both shared and modality-specific information in an end-to-end manner. We present PET…

Cited by 0SourceScholar
2025

CellCLIP - Learning Perturbation Effects in Cell Painting via Text-Guided Contrastive Learning

NeurIPS 2025poster

High-content screening (HCS) assays based on high-throughput microscopy techniques such as Cell Painting have enabled the interrogation of cells' morphological responses to perturbations at an unprecedented scale. The collection of such data promises to facilitate a better understanding of the relat…

Cited by 0SourcecodeScholar
2022

Moment Matching Deep Contrastive Latent Variable Models

AISTATS 2022poster

In the contrastive analysis (CA) setting, machine learning practitioners are specifically interested in discovering patterns that are enriched in a target dataset as compared to a background dataset generated from sources of variation irrelevant to the task at hand. For example, a biomedical data an…