A PyTorch Library for Accelerating 3D Deep Learning Research
- pytorch
- 3d-deep-learning
- neural-networks
- differentiable-rendering
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A PyTorch Library for Accelerating 3D Deep Learning Research
Deep probabilistic analysis of single-cell and spatial omics data
Graph-linked unified embedding for single-cell multi-omics data integration
cell detection in calcium imaging recordings
OPEM (Open Source PEM Fuel Cell Simulation Tool)
Automated 3D cell detection in very large images
A tool for cell instance aware segmentation in densely packed 3D volumetric images
Inner ear models for Python
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
Nellie: Automated organelle segmentation, tracking, and hierarchical feature extraction in 2D/3D live-cell microscopy
Autonomous multi-agent framework to optimize scientific software
MCP server for spatial transcriptomics analysis through natural language interfaces.
Multigrate: multiomic data integration for single-cell genomics
Fast, deterministic cell-type deconvolution for million-bin spatial transcriptomics