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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…

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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…

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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…