LHSD uses spectral filtering on the log-density Hessian to isolate tangent directions from noise and estimate local intrinsic dimension scalably via Stochastic Lanczos Quadrature.
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Unbalanced Schrödinger Bridge (USB) provides a tractable, simulation-free solution to the Branching Schrödinger Bridge problem for modeling discrete birth-death dynamics at single-cell resolution from snapshot data.
Diffusion models solve noisy (non)linear inverse problems via approximated posterior sampling that blends diffusion steps with manifold gradients without strict consistency projection.
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Local Hessian Spectral Filtering for Robust Intrinsic Dimension Estimation
LHSD uses spectral filtering on the log-density Hessian to isolate tangent directions from noise and estimate local intrinsic dimension scalably via Stochastic Lanczos Quadrature.
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Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots
Unbalanced Schrödinger Bridge (USB) provides a tractable, simulation-free solution to the Branching Schrödinger Bridge problem for modeling discrete birth-death dynamics at single-cell resolution from snapshot data.
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Diffusion Posterior Sampling for General Noisy Inverse Problems
Diffusion models solve noisy (non)linear inverse problems via approximated posterior sampling that blends diffusion steps with manifold gradients without strict consistency projection.