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Efficiently generating statistically independent samples from an unnormalized probability distribution, such as equilibrium samples of …

The dynamical formulation of the optimal transport can be extended through various choices of the underlying geometry (kinetic energy), …

We present FoldFlow a novel flow matching model for protein design. We present theory and practical tricks for flow models over SE(3)^N. Empirically, we validate these models on protein backbone generation of up to 300 amino acids leading to high-quality designable, diverse, and novel samples.

We present simulation-free score and flow matching ([SF]2M), a simulation-free objective for inferring stochastic dynamics given …

Trellis is a tree-based earth mover’s distance method for understanding estimating treatment effects from single cell data. In this work we apply it to colorectal cancer PDOS and investigate the chemoprotection induced by cancer-associated fibroblasts.

One of the grand challenges of cell biology is inferring the gene regulatory network (GRN) which describes interactions between genes …

The scattering transform is a multilayered wavelet-based deep learning architecture that acts as a model of convolutional neural …

Efficient computation of optimal transport distance between distributions is of growing importance in data science. Sinkhorn-based …