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Diffusion condensation is a dynamic process that yields a sequence of multiscale data representations that aim to encode meaningful …

Due to commonalities in pathophysiology, age-related macular degeneration (AMD) represents a uniquely accessible model to investigate …

We present methods for learning simple flows over R^d with optimal transport conditional flow matching (OT-CFM). Training with this objective leads to imprved results on a variety of conditional and unconditional generation tasks, such as inferring single cell dynamics, unsupervised image translation, and Schrodinger bridge inference.

While numerous methods have been proposed for computing distances between probability distributions in Euclidean space, relatively …

We present a method called Manifold Interpolating Optimal-Transport Flow (MIOFlow) that learns stochastic, continuous population …

In modern relational machine learning it is common to encounter large graphs that arise via interactions or similarities between …

Checkpoint inhibitors (CPIs) targeting programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen 4 …

As the biomedical community produces datasets that are increasingly complex and high dimensional, there is a need for more …