3 citations · 5 across the 7 of their papers we have counts for
7 papers
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…
ContextFlow: Context-Aware Flow Matching For Trajectory Inference From Spatial Omics Data
Santanu Subhash Rathod, Francesco Ceccarelli, Sean B. Holden +3
Inferring trajectories from longitudinal spatially-resolved omics data is fundamental to understanding the dynamics of structural and functional tissue changes in development, rege…
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…
Predicting Treatment Adherence of Tuberculosis Patients at Scale
Mihir Kulkarni, Satvik Golechha, Rishi Raj +9
Tuberculosis (TB), an infectious bacterial disease, is a significant cause of death, especially in low-income countries, with an estimated ten million new cases reported globally i…
Scheduling to Learn In An Unsupervised Online Streaming Model
R. Vaze, Santanu Rathod
An unsupervised online streaming model is considered where samples arrive in an online fashion over slots. There are classifiers, whose confusion matrices are unknown a pri…
On reducing the order of arm-passes bandit streaming algorithms under memory bottleneck
Santanu Rathod
In this work we explore multi-arm bandit streaming model, especially in cases where the model faces resource bottleneck. We build over existing algorithms conditioned by limited ar…
Global Convergence Using Policy Gradient Methods for Model-free Markovian Jump Linear Quadratic Control
Santanu Rathod, Manoj Bhadu, Abir De
Owing to the growth of interest in Reinforcement Learning in the last few years, gradient based policy control methods have been gaining popularity for Control problems as well. An…