Machine Learning for Spatially Resolved High-dimensional Biology

This workshop examines machine learning for spatial transcriptomic, proteomic and imaging measurements. Topics include tissue geometry, integration across modalities, cell communication, noise, sparse data, interpretability, uncertainty and benchmarks at cellular, tissue and atlas scales. Session: 08:30–18:15 (Europe/Paris). A paid NeurIPS virtual pass includes workshop livestreams; on-site access follows the host-location registration rules.