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Temporal scRNA-seq Modeling under Sparsity on DR (Drosophila) Hard Sparse Modeling

32.68Score (t=2)PRESCIENT
28.592829.653930.71531.7761May 20, 2026

Evaluation results

MethodLinks
PRESCIENT2026.0532.6832.3633.0835.5134.1938.12
PRESCIENT2026.0532.6832.3633.0835.5134.1938.12
LGP-OTvarsigma(t)=varsigma2026.0530.7732.1534.1435.6636.7739.21
PI-SDE2026.0530.3430.8232.7134.1834.5538.9
PI-SDE2026.0530.3430.8232.7134.1834.5538.9
VGFM2026.0530.2731.333.3635.6235.3638.47
VGFM2026.0530.2731.333.3635.6235.3638.47
LGP-OT (ς(t) = 0.1)ς(t)=0.12026.0530.1431.2833.2934.9334.8838.79
LGP-OTvarsigma(t)=0.12026.0530.1431.2833.2934.9334.8838.79
scNODE2026.0529.9530.7132.8834.8234.6338.26
scNODE2026.0529.9530.7132.8834.8234.6338.26
MIOFlow2026.0529.7430.9732.8435.2536.7841.43
MIOFlow2026.0529.7430.9732.8435.2536.7841.43
LGP-OT (w. time)Cell-time variability=true2026.0529.5930.4832.333.8333.6837.71
LGP-OTfeatures=w. time2026.0529.5930.4832.333.8333.6837.71
LGP-OT2026.0529.430.6132.3333.7833.8538.17
LGP-OT2026.0529.430.6132.3333.7833.8538.17
LGP-OT (w. time + type)Cell-time variability=true, Cell-type conditioning=true2026.0528.8430.4832.233.7733.5237.88
LGP-OTfeatures=w. time + type2026.0528.8430.4832.233.7733.5237.88
LGP-OT (w. type)Cell-type conditioning=true2026.0528.7530.3932.1933.7533.5237.82
LGP-OTfeatures=w. type2026.0528.7530.3932.1933.7533.5237.82