mlsanityData to 7 Oct 2026

FreeBridge: Variational Schr"odinger Bridges for Cellular Transition Dynamics

arXiv 2606.11286 ↗First posted 9 Jun 2026cs.LG cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

High-content imaging assays quantify cellular responses to chemical and genetic perturbations, yet continuous trajectories of individual cells are unobservable because cells are chemically fixed at acquisition. Perturbation modeling therefore reduces to inferring stochastic transport between control and treated populations observed only as separate marginals. While recent generative models achieve strong end-point alignment, boundary consistency does not determine intermediate evolution: multiple stochastic processes may connect identical marginals while traversing regions unsupported by observed single-cell morphologies. We introduce FreeBridge, a Schr"odinger Bridge formulation for single-cell transition modeling under endpoint-only supervision. FreeBridge defines atomic states as instance-segmented single-cell representations, establishing a fixed cellular manifold, and learns stochastic transport constrained within this geometry via empirical latent support regularization. Across BBBC021, RxRx1, and JUMP, FreeBridge maintains competitive or improved endpoint fidelity and mechanism-of-action retention under a unified evaluation protocol; on BBBC021, it further reduces intermediate support violations. These findings highlight the importance of geometric grounding for biologically interpretable perturbation dynamics. Project page: https://y-research-sbu.github.io/FreeBridge/.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 25 references that are in the map. First posted on arXiv 9 Jun 2026.

Builds on

16 of 25 references.

References · 16

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2022Flow Matching for Generative Modelingcited by 5,426
  5. 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,550
  6. 2018Demystifying MMD GANscited by 1,268
  7. 2013A survey of the Schr"odinger problem and some of its connections with optimal transportcited by 286
  8. 2014On the relation between optimal transport and Schr"odinger bridges: A stochastic control viewpointcited by 99
  9. 2024How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunitiescited by 50
  10. 2023RxRx1: A Dataset for Evaluating Experimental Batch Correction Methodscited by 45
  11. 2023Generalized Schr"odinger Bridge Matchingcited by 40
  12. 2025CellFlux: Simulating Cellular Morphology Changes via Flow Matchingcited by 19
4 more
  1. 2025Ouroboros: Single-step Diffusion Models for Cycle-consistent Forward and Inverse Renderingcited by 16
  2. 2023PhenDiff: Revealing Subtle Phenotypes with Diffusion Models in Real Imagescited by 10
  3. 2025Scale Where It Matters: Training-Free Localized Scaling for Diffusion Modelscited by 6
  4. 2026Let EEG Models Learn EEGcited by 6

Built on by

Not cited yet.