Bharat Srikishan — accepted AI-conference papers

2025

Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout

Bharat Srikishan, Daniel O'Malley, Mohamed Mehana, Nicholas Lubbers, Nikhil Muralidhar

ICLR 2025poster

Modeling the evolution of physical systems is critical to many applications in science and engineering. As the evolution of these systems is governed by partial differential equations (PDEs), there are a number of computational simulations which resolve these systems with high accuracy. However, as…

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗

2024

Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation

Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar

AAAI 2024technical

Deep learning architectures have achieved state-of-the-art (SOTA) performance on computer vision tasks such as object detection and image segmentation. This may be attributed to the use of over-parameterized, monolithic deep learning architectures executed on large datasets. Although such large arch…

Cited by 1 Source ↗PDF ↗code ↗Scholar ↗