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2020 – today
- 2024
[j4]Ahasanul Haque, Naznin Akther, Irfanuzzaman Khan, Khushbu Agarwal
, Nazim Uddin:
Artificial Intelligence in Retail Marketing: Research Agenda Based on Bibliometric Reflection and Content Analysis (2000-2023). Informatics 11(4): 74 (2024)- [c21]Stefan Dernbach, Khushbu Agarwal, Alejandro Zuniga, Michael Henry, Sutanay Choudhury:
GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding. AAAI Spring Symposia 2024: 82-89 - [c20]Henry W. Sprueill, Carl Edwards, Khushbu Agarwal, Mariefel V. Olarte, Udishnu Sanyal, Conrad Johnston, Hongbin Liu, Heng Ji, Sutanay Choudhury:
CHEMREASONER: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback. ICML 2024 - [i13]Stefan Dernbach, Khushbu Agarwal, Alejandro Zuniga, Michael Henry, Sutanay Choudhury:
GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding. CoRR abs/2402.06764 (2024) - [i12]Henry W. Sprueill, Carl Edwards, Khushbu Agarwal, Mariefel V. Olarte, Udishnu Sanyal, Conrad Johnston, Hongbin Liu, Heng Ji, Sutanay Choudhury:
ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback. CoRR abs/2402.10980 (2024) - 2023
- [c19]Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K. Reddy:
A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks. IJCAI 2023: 3875-3883 - [c18]Sutanay Choudhury, Khushbu Agarwal, Colby Ham, Suzanne Tamang:
MediSage: An AI Assistant for Healthcare via Composition of Neural-Symbolic Reasoning Operators. WWW (Companion Volume) 2023: 258-261 - 2022
- [j3]Sai Pushpak Nandanoori, Sheng Guan, Soumya Kundu, Seemita Pal, Khushbu Agarwal, Yinghui Wu, Sutanay Choudhury:
Graph Neural Network and Koopman Models for Learning Networked Dynamics: A Comparative Study on Power Grid Transients Prediction. IEEE Access 10: 32337-32349 (2022) - [c17]Ping Wang, Tian Shi, Khushbu Agarwal, Sutanay Choudhury, Chandan K. Reddy:
Attention-based aspect reasoning for knowledge base question answering on clinical notes. BCB 2022: 10:1-10:6 - [c16]Sayak Mukherjee, Sai Pushpak Nandanoori, Sheng Guan, Khushbu Agarwal, Subhrajit Sinha, Soumya Kundu, Seemita Pal, Yinghui Wu, Draguna L. Vrabie, Sutanay Choudhury:
Learning Distributed Geometric Koopman Operator for Sparse Networked Dynamical Systems. LoG 2022: 45 - [i11]Sai Pushpak Nandanoori, Sheng Guan, Soumya Kundu, Seemita Pal, Khushbu Agarwal, Yinghui Wu, Sutanay Choudhury:
Graph Neural Network and Koopman Models for Learning Networked Dynamics: A Comparative Study on Power Grid Transients Prediction. CoRR abs/2202.08065 (2022) - [i10]Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K. Reddy:
Pseudo-Poincaré: A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks. CoRR abs/2206.04285 (2022) - 2021
- [c15]Sutanay Choudhury, Khushbu Agarwal, Colby Ham, Pritam Mukherjee, Siyi Tang, Sindhu Tipirneni, Veysel Kocaman, Suzanne Tamang, Robert Rallo, Chandan K. Reddy:
Tracking the Evolution of COVID-19 via Temporal Comorbidity Analysis from Multi-Modal Data. AMIA 2021 - [c14]Sai Pushpak Nandanoori, Seemita Pal, Subhrajit Sinha, Soumya Kundu, Khushbu Agarwal, Sutanay Choudhury:
Data-driven Distributed Learning of Multi-agent Systems: A Koopman Operator Approach. CDC 2021: 5059-5066 - [c13]Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, Chandan K. Reddy:
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks. WWW 2021: 2946-2957 - [i9]Ping Wang, Tian Shi, Khushbu Agarwal, Sutanay Choudhury, Chandan K. Reddy:
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes. CoRR abs/2108.00513 (2021) - 2020
- [c12]Sai Pushpak Nandanoori, Soumya Kundu, Seemita Pal, Khushbu Agarwal, Sutanay Choudhury:
Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes. SmartGridComm 2020: 1-6 - [i8]Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, Chandan K. Reddy:
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks. CoRR abs/2007.11192 (2020) - [i7]Sai Pushpak Nandanoori, Soumya Kundu, Seemita Pal, Khushbu Agarwal, Sutanay Choudhury:
Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes. CoRR abs/2007.11717 (2020)
2010 – 2019
- 2019
- [i6]Khushbu Agarwal, Tome Eftimov, Raghavendra Addanki, Sutanay Choudhury, Suzanne Tamang, Robert Rallo:
Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics. CoRR abs/1907.08650 (2019) - 2018
- [c11]Sutanay Choudhury, Sumit Purohit, Peng Lin, Yinghui Wu, Lawrence B. Holder, Khushbu Agarwal:
Percolator: Scalable Pattern Discovery in Dynamic Graphs. WSDM 2018: 759-762 - [i5]Cliff A. Joslyn, Michael Robinson, J. Smart, Khushbu Agarwal, David Bridgeland, Adam Brown, Sutanay Choudhury, Brett A. Jefferson, Brenda Praggastis, Emilie Purvine, William P. Smith, Dimitri Zarzhitsky:
HyperThesis: Topological Hypothesis Management in a Hypergraph Knowledgebase. TAC 2018 - 2017
- [c10]Sutanay Choudhury, Khushbu Agarwal, Sumit Purohit, Baichuan Zhang, Meg Pirrung, William P. Smith, Mathew Thomas:
NOUS: Construction and Querying of Dynamic Knowledge Graphs. ICDE 2017: 1563-1565 - [c9]Vito Giovanni Castellana, Marco Minutoli, Shreyansh Bhatt, Khushbu Agarwal, Arthur Bleeker, John Feo, Daniel G. Chavarría-Miranda, David J. Haglin:
High-Performance Data Analytics Beyond the Relational and Graph Data Models with GEMS. IPDPS Workshops 2017: 1029-1038 - 2016
- [i4]Baichuan Zhang, Sutanay Choudhury, Mohammad Al Hasan, Xia Ning, Khushbu Agarwal, Sumit Purohit, Paola Gabriela Pesntez Cabrera:
Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs. CoRR abs/1601.03778 (2016) - [i3]Sutanay Choudhury, Khushbu Agarwal, Sumit Purohit, Baichuan Zhang, Meg Pirrung, William P. Smith, Mathew Thomas:
NOUS: Construction and Querying of Dynamic Knowledge Graphs. CoRR abs/1606.02314 (2016) - 2015
- [c8]Abhinav Vishnu, Khushbu Agarwal:
Large Scale Frequent Pattern Mining Using MPI One-Sided Model. CLUSTER 2015: 138-147 - [c7]Sutanay Choudhury, Lawrence B. Holder, George Chin Jr., Khushbu Agarwal, John Feo:
A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs. EDBT 2015: 157-168 - [i2]Sutanay Choudhury, Lawrence B. Holder, George Chin Jr., Khushbu Agarwal, John Feo:
A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs. CoRR abs/1503.00849 (2015) - 2014
- [j2]Khushbu Agarwal, Sharma Poorva, Jinliang Ma, Chaomei Lo, Ian Gorton, Yan Liu:
Reveal: An Extensible Reduced-Order Model Builder for Simulation and Modeling. Comput. Sci. Eng. 16(2): 44-53 (2014) - [c6]Selim Ciraci, Jeff A. Daily, Khushbu Agarwal, Jason C. Fuller, Laurentiu Marinovici, Andrew Fisher:
Synchronization Algorithms for Co-simulation of Power Grid and Communication Networks. MASCOTS 2014: 355-364 - [c5]Selim Ciraci, Jeff A. Daily, Jason C. Fuller, Andrew Fisher, Laurentiu Marinovici, Khushbu Agarwal:
FNCS: a framework for power system and communication networks co-simulation. SpringSim (TMS-DEVS) 2014: 36 - [i1]Sutanay Choudhury, Lawrence B. Holder, George Chin Jr., Patrick Mackey, Khushbu Agarwal, John Feo:
Query Optimization for Dynamic Graphs. CoRR abs/1407.3745 (2014) - 2013
- [c4]Daniel G. Chavarría-Miranda, Khushbu Agarwal, Tjerk P. Straatsma:
Scalable PGAS Metadata Management on Extreme Scale Systems. CCGRID 2013: 103-111 - 2011
- [c3]Jian Yin, Khushbu Agarwal, Manoj Krishnan, Daniel G. Chavarría-Miranda, Ian Gorton, Tom Epperly:
Implementing High Performance Remote Method Invocation in CCA. CLUSTER 2011: 547-551 - [c2]Khushbu Agarwal, Jared M. Chase, Karen L. Schuchardt, Timothy D. Scheibe, Bruce J. Palmer, Todd O. Elsethagen:
Design and implementation of "many parallel task" hybrid subsurface model. MTAGS@SC 2011: 25-32 - 2010
- [j1]Anuj R. Shah, Khushbu Agarwal, Erin S. Baker, Mudita Singhal, Anoop M. Mayampurath, Yehia M. Ibrahim, Lars J. Kangas, Matthew E. Monroe, Rui Zhao, Mikhail E. Belov, Gordon A. Anderson, Richard D. Smith:
Machine learning based prediction for peptide drift times in ion mobility spectrometry. Bioinform. 26(13): 1601-1607 (2010) - [c1]Sriram Krishnamoorthy, Khushbu Agarwal:
Scalable Communication Trace Compression. CCGRID 2010: 408-417
Coauthor Index
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last updated on 2024-12-02 21:30 CET by the dblp team
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