Connectivity Inference in Mass Spectrometry Based Structure Determination. - Deepesh Agarwal; Júlio César Silva Araújo; Christelle Caillouet; Frédéric Cazals; David Coudert; Stéphane Pérennes (ESA, 2013)

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 (2015)

Addressing Uncertainties within Active Learning for Industrial IoT. - Deepesh Agarwal; Pravesh Srivastava; Sergio Martin del Campo; Balasubramaniam Natarajan; Babji Srinivasan (WF-IoT, 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)

Active Learning for Node Classification using a Convex Optimization approach. - Deepesh Agarwal; Balasubramaniam Natarajan (BigDataService, 2022)

Impacts of Behavioral Biases on Active Learning Strategies. - Deepesh Agarwal; Obdulia Covarrubias-Zambrano; Stefan H. Bossmann; Balasubramaniam Natarajan (ICAIIC, 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)

Foundational Models for Fault Diagnosis of Electrical Motors. - Sriram Anbalagan; Deepesh Agarwal; Balasubramaniam Natarajan; Babji Srinivasan (CoRR, 2023)

Active Foundational Models for Fault Diagnosis of Electrical Motors. - Sriram Anbalagan; Sai Shashank GP; Deepesh Agarwal; Balasubramaniam Natarajan; Babji Srinivasan (CoRR, 2023)

A general framework for quantifying aleatoric and epistemic uncertainty in graph neural networks. - Sai Munikoti; Deepesh Agarwal; Laya Das; Balasubramaniam Natarajan (Neurocomputing, 2023)

Tracking and handling behavioral biases in active learning frameworks. - Deepesh Agarwal; Balasubramaniam Natarajan (Inf. Sci., 2023)

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., 2024)

Inductive graph neural network framework for imputation of single-cell RNA sequencing data. - Boneshwar V. K; Deepesh Agarwal; Bala Natarajan; Babji Srinivasan (Comput. Chem. Eng., 2025)