activity
20222026
collaborators

5 papers

cs.LG2026

SSM Adapters via Hankel Reduced-order Modeling: Injection Site Determines Task Suitability in Long-Context Fine-Tuning

Omanshu Thapliyal

While parameter-efficient fine-tuning (PEFT) typically targets attention projectors, its efficacy for tasks requiring sequential state accumulation remains under-explored. We exami…

eess.SY2026

Safe Navigation using Neural Radiance Fields via Reachable Sets

Omanshu Thapliyal, Malarvizhi Sankaranarayanasamy, Ravigopal Vennelakanti

Safe navigation in cluttered environments is an important challenge for autonomous systems. Robots navigating through obstacle ridden scenarios need to be able to navigate safely i…

eess.SY2024

An Algorithm for Distributed Computation of Reachable Sets for Multi-Agent Systems

Omanshu Thapliyal, Shanelle Clarke, Inseok Hwang

In this paper, we consider the problem of distributed reachable set computation for multi-agent systems (MASs) interacting over an undirected, stationary graph. A full state-feedba…

eess.SY2022

Data-driven Cyberattack Synthesis against Network Control Systems

Omanshu Thapliyal, Inseok Hwang

Network Control Systems (NCSs) pose unique vulnerabilities to cyberattacks due to a heavy reliance on communication channels. These channels can be susceptible to eavesdropping, fa…

eess.SY2022

Approximating Reachable Sets for Neural Network based Models in Real-Time via Optimal Control

Omanshu Thapliyal, Inseok Hwang

In this paper, we present a data-driven framework for real-time estimation of reachable sets for control systems where the plant is modeled using neural networks (NNs). We utilize…