Laya Das

According to our database, Laya Das authored at least 21 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Challenges and Opportunities in Deep Reinforcement Learning With Graph Neural Networks: A Comprehensive Review of Algorithms and Applications.

Sai Munikoti, Deepesh Agarwal, Laya Das, Mahantesh Halappanavar, Balasubramaniam Natarajan

IEEE Trans. Neural Networks Learn. Syst., November, 2024

Uncertainty-aware deep learning for monitoring and fault diagnosis from synthetic data.

Laya Das, Blazhe Gjorgiev, Giovanni Sansavini

Reliab. Eng. Syst. Saf., 2024

2023

A testbed for studying the interactions between human operators and advanced control systems.

Ritu Ranjan, Laya Das, Niket S. Kaisare, Rajagopalan Srinivasan

Comput. Chem. Eng., October, 2023

Simulation-driven deep learning for locating faulty insulators in a power line.

Blazhe Gjorgiev, Laya Das, Seline Merkel, Martina Rohrer, Etienne Auger, Giovanni Sansavini

Reliab. Eng. Syst. Saf., 2023

A general framework for quantifying aleatoric and epistemic uncertainty in graph neural networks.

Sai Munikoti, Deepesh Agarwal, Laya Das, Balasubramaniam Natarajan

Neurocomputing, 2023

Anomaly detection for automated inspection of power line insulators.

Laya Das, Blazhe Gjorgiev, Giovanni Sansavini

CoRR, 2023

There is more to graphs than meets the eye: Learning universal features with self-supervision.

Laya Das, Sai Munikoti, Mahantesh Halappanavar

CoRR, 2023

Uncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines.

Laya Das, Blazhe Gjorgiev, Giovanni Sansavini

CoRR, 2023

2022

Scalable graph neural network-based framework for identifying critical nodes and links in complex networks.

Sai Munikoti, Laya Das, Balasubramaniam Natarajan

Neurocomputing, 2022

Object detection-based inspection of power line insulators: Incipient fault detection in the low data-regime.

Laya Das, Mohammad Hossein Saadat, Blazhe Gjorgiev, Etienne Auger, Giovanni Sansavini

CoRR, 2022

A unified theory of emergent equilibrium phenomena in active and passive matter.

Venkat Venkatasubramanian, Abhishek Sivaram, Laya Das

Comput. Chem. Eng., 2022

2021

Robust and efficient swarm communication topologies for hostile environments.

Vipul Mann, Abhishek Sivaram, Laya Das, Venkat Venkatasubramanian

Swarm Evol. Comput., 2021

Bayesian Graph Neural Network for Fast identification of critical nodes in Uncertain Complex Networks.

Sai Munikoti, Laya Das, Balasubramaniam Natarajan

Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021

2020

Graph neural network based approximation of Node Resiliency in complex networks.

Sai Munikoti, Laya Das, Balasubramaniam Natarajan

CoRR, 2020

Hidden representations in deep neural networks: Part 1. Classification problems.

Abhishek Sivaram, Laya Das, Venkat Venkatasubramanian

Comput. Chem. Eng., 2020

Hidden representations in deep neural networks: Part 2. Regression problems.

Laya Das, Abhishek Sivaram, Venkat Venkatasubramanian

Comput. Chem. Eng., 2020

2019

Data-Driven Approaches for Diagnosis of Incipient Faults in DC Motors.

Sai Munikoti, Laya Das, Balasubramaniam Natarajan, Babji Srinivasan

IEEE Trans. Ind. Informatics, 2019

A Framework for Efficient Information Aggregation in Smart Grid.

Amit Joshi, Laya Das, Balasubramaniam Natarajan, Babji Srinivasan

IEEE Trans. Ind. Informatics, 2019

2016

Multivariate Control Loop Performance Assessment With Hurst Exponent and Mahalanobis Distance.

Laya Das, Babji Srinivasan, Raghunathan Rengaswamy

IEEE Trans. Control. Syst. Technol., 2016

2015

On-line performance monitoring of PEM fuel cell using a fast EIS approach.

Laya Das, Babji Srinivasan, Raghunathan Rengaswamy

Proceedings of the American Control Conference, 2015

2014

Data driven approach for performance assessment of linear and nonlinear Kalman filters.

Laya Das, Babji Srinivasan, Raghunathan Rengaswamy

Proceedings of the American Control Conference, 2014