6 citations · 6 across the 3 of their papers we have counts for
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cs.LG2026
SplineFlow: Flow Matching for Dynamical Systems with B-Spline Interpolants
Santanu Subhash Rathod, Pietro Liò, Xiao Zhang
Flow matching is a scalable generative framework for characterizing continuous normalizing flows with wide-range applications. However, current state-of-the-art methods are not wel…
cs.LG2024
Predicting time-varying flux and balance in metabolic systems using structured neural-ODE processes
Santanu Rathod, Pietro Lio, Xiao Zhang
We develop a novel data-driven framework as an alternative to dynamic flux balance analysis, bypassing the demand for deep domain knowledge and manual efforts to formulate the opti…
cs.LG2020★ 6 cited
tvGP-VAE: Tensor-variate Gaussian Process Prior Variational Autoencoder
Alex Campbell, Pietro Liò
Variational autoencoders (VAEs) are a powerful class of deep generative latent variable model for unsupervised representation learning on high-dimensional data. To ensure computati…