3 papers
eess.SY2026
Integrating Lagrangian Neural Networks into the Dyna Framework for Reinforcement Learning
Shreya Das, Kundan Kumar, Muhammad Iqbal +4
Model-based reinforcement learning (MBRL) is sample-efficient but depends on the accuracy of the learned dynamics, which are often modeled using black-box methods that do not adher…
eess.SP2025
Statistical Linear Regression Approach to Kalman Filtering and Smoothing under Cyber-Attacks
Kundan Kumar, Muhammad Iqbal, Simo Särkkä
Remote state estimation in cyber-physical systems is often vulnerable to cyber-attacks due to wireless connections between sensors and computing units. In such scenarios, adversari…
eess.SY2025
Communication-Efficient Distributed Kalman Filtering using ADMM
Muhammad Iqbal, Kundan Kumar, Simo Särkkä
This paper addresses the problem of optimal linear filtering in a network of local estimators, commonly referred to as distributed Kalman filtering (DKF). The DKF problem is formul…