Update README.md

README.md

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 license: cc-by-nc-nd-4.0
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 <h1 align='center'>Branched Schrödinger Bridge Matching</h1>
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 First, we evaluate BranchSBM for navigating branched paths along the surface of a 3-dimensional LiDAR manifold, from an initial distribution to two distinct target distributions.
 
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 <p align="center"><em>Figure 3: Application of BranchSBM on Learning Branched Paths on a LiDAR Manifold.</em></p>
 
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 BranchSBM is uniquely positioned to model single-cell population dynamics where a homogeneous cell population (e.g., progenitor cells) differentiates into several distinct subpopulation branches, each of which independently undergoes growth dynamics. We demonstrate this capability on mouse hematopoiesis data.
 
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 <p align="center"><em>Figure 4: Application of BranchSBM on Modeling Differentiating Single-Cell Population Dynamics.</em></p>
 
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 First, we modeled two branches to two divergent subpopulations in the Clonidine-perturbed cells from the initial control DMSO-treated cells with BranchSBM and compared with single-branch SBM. 
 
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 <p align="center"><em>Figure 5: Results for Clonidine Perturbation Modeling with BranchSBM.</em></p>
 
 Finally, we used BranchSBM to model three branched trajectories in the Trametinib-perturbed cells from the initial control DMSO-treated cells.
 
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 <p align="center"><em>Figure 6: Results for Trametinib Perturbation Modeling with BranchSBM.</em></p>