1 citations · 1 across the 9 of their papers we have counts for
9 papers
Variational Outlier-Robust Gaussian Process Regression with Generative Modeling
Arslan Majal, Aamir Hussain Chughtai
Outliers can substantially distort Gaussian process regression (GPR) due to its conventional Gaussian observation likelihood, leading to inaccurate model learning and prediction. T…
Dictionary-Based Contrastive Learning for GNSS Jamming Detection
Zawar Hussain, Arslan Majal, Aamir Hussain Chughtai +1
Global Navigation Satellite System (GNSS) signals are fundamental in applications across navigation, transportation, and industrial networks. However, their extremely low received…
EMORF-II: Adaptive EM-based Outlier-Robust Filtering with Correlated Measurement Noise
Arslan Majal, Aamir Hussain Chughtai, Muhammad Tahir
We present a learning-based outlier-robust filter for a general setup where the measurement noise can be correlated. Since it is an enhanced version of EM-based outlier robust filt…
Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications
Aamir Hussain Chughtai
State estimation or filtering serves as a fundamental task to enable intelligent decision-making in applications such as autonomous vehicles, robotics, healthcare monitoring, smart…
Trajectory Reconstruction through a Gaussian Adaptive Selective Outlier Rejecting Smoother
Arslan Majal, Aamir Hussain Chughtai
Trajectory Reconstruction (TR) is vital for accurately mapping movement patterns and validating analyses, especially in fields like robotics, biomechanics, and environmental tracki…
EMORF/S: EM-Based Outlier-Robust Filtering and Smoothing With Correlated Measurement Noise
Aamir Hussain Chughtai, Muhammad Tahir, Momin Uppal
In this article, we consider the problem of outlier-robust state estimation where the measurement noise can be correlated. Outliers in data arise due to many reasons like sensor ma…
Bayesian Heuristics for Robust Spatial Perception
Aamir Hussain Chughtai, Muhammad Tahir, Momin Uppal
Spatial perception is a key task in several machine intelligence applications such as robotics and computer vision. In general, it involves the nonlinear estimation of hidden varia…
Variational-Based Nonlinear Bayesian Filtering with Biased Observations
Aamir Hussain Chughtai, Arslan Majal, Muhammad Tahir +1
State estimation of dynamical systems is crucial for providing new decision-making and system automation information in different applications. However, the assumptions on the stan…
Outlier-Robust Filtering For Nonlinear Systems With Selective Observations Rejection
Aamir Hussain Chughtai, Muhammad Tahir, Momin Uppal
Considering a common case where measurements are obtained from independent sensors, we present a novel outlier-robust filter for nonlinear dynamical systems in this work. The propo…