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Khushbu Agarwal
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2020 – today
- 2024
- [c20]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 - [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 2024-06-04 21:31 CEST by the dblp team
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