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Neeraj Kumar
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Publications
- 2024
- [c13]Junjie Kang, Jinsong Wu, Shiqi Jiang, Neeraj Kumar, Brij Bhooshan Gupta:
Region-Controlled Style Transfer. ICC 2024: 19-24 - [i13]Andrew D. McNaughton, Gautham Ramalaxmi, Agustin Kruel, Carter R. Knutson, Rohith Anand Varikoti, Neeraj Kumar:
CACTUS: Chemistry Agent Connecting Tool-Usage to Science. CoRR abs/2405.00972 (2024) - 2023
- [j29]Rohith Anand Varikoti, Katherine J. Schultz, Chathuri J. Kombala, Agustin Kruel, Kristoffer R. Brandvold, Mowei Zhou, Neeraj Kumar:
Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV-2 main protease. J. Comput. Aided Mol. Des. 37(8): 339-355 (2023) - [j28]Rajendra P. Joshi, Katherine J. Schultz, Jesse William Wilson, Agustin Kruel, Rohith Anand Varikoti, Chathuri J. Kombala, Daniel W. Kneller, Stephanie Galanie, Gwyndalyn Phillips, Qiu Zhang, Leighton Coates, Jyothi Parvathareddy, Surekha Surendranathan, Ying Kong, Austin Clyde, Arvind Ramanathan, Colleen B. Jonsson, Kristoffer R. Brandvold, Mowei Zhou, Martha S. Head, Andrey Kovalevsky, Neeraj Kumar:
AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2. J. Chem. Inf. Model. 63(5): 1438-1453 (2023) - [j27]Andrew D. McNaughton, Rajendra P. Joshi, Carter R. Knutson, Fnu Anubhav, Kevin J. Luebke, Jeremiah P. Malerich, Peter B. Madrid, Neeraj Kumar:
Machine Learning Models for Predicting Molecular UV-Vis Spectra with Quantum Mechanical Properties. J. Chem. Inf. Model. 63(5): 1462-1471 (2023) - [i12]Agustin Kruel, Andrew D. McNaughton, Neeraj Kumar:
Scaffold-Based Multi-Objective Drug Candidate Optimization. CoRR abs/2301.07175 (2023) - 2022
- [j20]Austin Clyde, Stephanie Galanie, Daniel W. Kneller, Heng Ma, Yadu N. Babuji, Ben Blaiszik, Alexander Brace, Thomas S. Brettin, Kyle Chard, Ryan Chard, Leighton Coates, Ian T. Foster, Darin Hauner, Vilmos Kertesz, Neeraj Kumar, Hyungro Lee, Zhuozhao Li, André Merzky, Jurgen G. Schmidt, Li Tan, Mikhail Titov, Anda Trifan, Matteo Turilli, Hubertus Van Dam, Srinivas C. Chennubhotla, Shantenu Jha, Andrey Kovalevsky, Arvind Ramanathan, Martha S. Head, Rick Stevens:
High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor. J. Chem. Inf. Model. 62(1): 116-128 (2022) - [c8]Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Érica Teixeira Prates, Verónica G. Melesse Vergara, Manesh Shah, Austin Clyde, Thomas S. Brettin, Wibe Albert de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown:
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery. ICLR 2022 - [i9]Andrew D. McNaughton, Mridula S. Bontha, Carter R. Knutson, Jenna A. Pope, Neeraj Kumar:
De novo design of protein target specific scaffold-based Inhibitors via Reinforcement Learning. CoRR abs/2205.10473 (2022) - [i8]Carter Knutson, Gihan Panapitiya, Rohith Anand Varikoti, Neeraj Kumar:
Dynamic Molecular Graph-based Implementation for Biophysical Properties Prediction. CoRR abs/2212.09991 (2022) - 2021
- [j13]Akash Sharma, Neeraj Kumar, Ayush Kumar, Karan Dikshit, Kusum Tharani, Bharat Singh:
Comparative investigation of machine learning algorithms for detection of epileptic seizures. Intell. Decis. Technol. 15(2): 269-279 (2021) - [j12]Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon:
Co-design Center for Exascale Machine Learning Technologies (ExaLearn). Int. J. High Perform. Comput. Appl. 35(6): 598-616 (2021) - [i7]Logan T. Ward, Jenna A. Bilbrey, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman:
Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19. CoRR abs/2102.04977 (2021) - [i6]Rajendra P. Joshi, Neeraj Kumar:
Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspective. CoRR abs/2102.06045 (2021) - [i5]Jenna A. Bilbrey, Logan T. Ward, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman:
Evening the Score: Targeting SARS-CoV-2 Protease Inhibition in Graph Generative Models for Therapeutic Candidates. CoRR abs/2105.10489 (2021) - [i4]Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Érica T. Prates, Manesh Shah, Verónica G. Melesse Vergara, Austin Clyde, Thomas S. Brettin, Wibe A. de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown:
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery. CoRR abs/2106.02190 (2021) - [i2]Luca Pion-Tonachini, Kristofer E. Bouchard, Héctor García Martín, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko M. Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel B. Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus H. Zwart, Neeraj Kumar, Amy Justice, Claire J. Tomlin, Daniel A. Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Kenneth Kreutz-Delgado, Michael W. Mahoney, James B. Brown:
Learning from learning machines: a new generation of AI technology to meet the needs of science. CoRR abs/2111.13786 (2021) - [i1]Carter Knutson, Mridula Bontha, Jenna A. Bilbrey, Neeraj Kumar:
Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks. CoRR abs/2111.15144 (2021)
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