Deepesh Agarwal

According to our database, Deepesh Agarwal authored at least 12 papers between 2013 and 2024.

Collaborative distances:

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

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

2023

Tracking and handling behavioral biases in active learning frameworks.

Deepesh Agarwal, Balasubramaniam Natarajan

Inf. Sci., September, 2023

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

Sai Munikoti, Deepesh Agarwal, Laya Das, Balasubramaniam Natarajan

Neurocomputing, 2023

Active Foundational Models for Fault Diagnosis of Electrical Motors.

Sriram Anbalagan, Sai Shashank GP, Deepesh Agarwal, Balasubramaniam Natarajan, Babji Srinivasan

CoRR, 2023

Foundational Models for Fault Diagnosis of Electrical Motors.

Sriram Anbalagan, Deepesh Agarwal, Balasubramaniam Natarajan, Babji Srinivasan

CoRR, 2023

2022

A Non-Invasive Hydration Monitoring Technique Using Microwave Transmission and Data-Driven Approaches.

Deepesh Agarwal, Philip Randall, Zachary White, Bayleigh Bisnette, Jenalee Dickson, Cross Allen, Faraz Chamani, Punit Prakash, Carl Ade, Balasubramaniam Natarajan

Sensors, 2022

Impacts of Behavioral Biases on Active Learning Strategies.

Deepesh Agarwal, Obdulia Covarrubias-Zambrano, Stefan H. Bossmann, Balasubramaniam Natarajan

Proceedings of the 2022 International Conference on Artificial Intelligence in Information and Communication, 2022

Active Learning for Node Classification using a Convex Optimization approach.

Deepesh Agarwal, Balasubramaniam Natarajan

Proceedings of the Eighth IEEE International Conference on Big Data Computing Service and Applications, 2022

2021

Addressing practical challenges in Active Learning via a hybrid query strategy.

Deepesh Agarwal, Pravesh Srivastava, Sergio Martin del Campo, Balasubramaniam Natarajan, Babji Srinivasan

CoRR, 2021

Addressing Uncertainties within Active Learning for Industrial IoT.

Deepesh Agarwal, Pravesh Srivastava, Sergio Martin del Campo, Balasubramaniam Natarajan, Babji Srinivasan

Proceedings of the 7th IEEE World Forum on Internet of Things, 2021

2015

Topics in mass spectrometry based structure determination. (Sur quelques problèmes algorithmiques relatifs à la détermination de structure à partir de données de spectrométrie de masse).

Deepesh Agarwal

PhD thesis, 2015

2013

Connectivity Inference in Mass Spectrometry Based Structure Determination.

Deepesh Agarwal, Júlio César Silva Araújo, Christelle Caillouet, Frédéric Cazals, David Coudert, Stéphane Pérennes

Proceedings of the Algorithms - ESA 2013, 2013