3 papers
math.OC2026
Scalable Deep Unfolding of Conic Optimizers
Alex Oshin, Rahul Vodeb Ghosh, Evangelos A. Theodorou
Deep unfolding (DU) accelerates iterative optimizers by introducing learnable components and training them through unrolled iterations, but extending DU to the large-scale semidefi…
physics.flu-dyn2026
Learning Flow Distributions via Projection-Constrained Diffusion on Manifolds
Noah Trupin, Rahul Ghosh, Aadi Jangid
We present a generative modeling framework for synthesizing physically feasible two-dimensional incompressible flows under arbitrary obstacle geometries and boundary conditions. Wh…
cs.LG2024
Hierarchical Conditional Multi-Task Learning for Streamflow Modeling
Shaoming Xu, Arvind Renganathan, Ankush Khandelwal +9
Streamflow, vital for water resource management, is governed by complex hydrological systems involving intermediate processes driven by meteorological forces. While deep learning m…