5 papers
CHAMMI-75: Pre-training multi-channel models with heterogeneous microscopy images
Vidit Agrawal, John Peters, Tyler N. Thompson +13
Quantifying cell morphology using images and machine learning has proven to be a powerful tool to study the response of cells to treatments. However, models used to quantify cellul…
Shortest-Path Flow Matching with Mixture-Conditioned Bases for OOD Generalization to Unseen Conditions
Andrea Rubbi, Amir Akbarnejad, Mohammad Vali Sanian +10
Robust generalization under distribution shift remains a key challenge for conditional generative modeling: conditional flow-based methods often fit the training conditions well bu…
SIGMMA: Hierarchical Graph-Based Multi-Scale Multi-modal Contrastive Alignment of Histopathology Image and Spatial Transcriptome
Dabin Jeong, Amirhossein Vahidi, Ciro RamÃrez-Suástegui +11
Recent advances in computational pathology have leveraged vision-language models to learn joint representations of Hematoxylin and Eosin (HE) images with spatial transcriptomic (ST…
3D-Guided Scalable Flow Matching for Generating Volumetric Tissue Spatial Transcriptomics from Serial Histology
Mohammad Vali Sanian, Arshia Hemmat, Amirhossein Vahidi +9
A scalable and robust 3D tissue transcriptomics profile can enable a holistic understanding of tissue organization and provide deeper insights into human biology and disease. Most…
MEENA (PersianMMMU): Multimodal-Multilingual Educational Exams for N-level Assessment
Omid Ghahroodi, Arshia Hemmat, Marzia Nouri +8
Recent advancements in large vision-language models (VLMs) have primarily focused on English, with limited attention given to other languages. To address this gap, we introduce MEE…