Lijing Wang

23 papers A* 6A 2B 2Journal 9Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Assessing the Macro and Micro Effects of Random Seeds on Fine-Tuning Large Language Models.
CoRR
Hao Zhou, Guergana Savova, Lijing Wang
2025 B conf
KEGNN: Knowledge-Enhanced Graph Neural Networks for User Engagement Prediction.
ICMR
Ching-Hao Fan, Hao Zhou, Yao Sun, Geovanny Palomino Roldan, Olga Kokshagina, Marc Santolini, Lijing Wang
2025 — conf
When Artificial Intelligence Meets Human Intelligence: Topics and Sentiments about ChatGPT in Online Knowledge Sharing Communities.
HICSS
Yao Sun, Lijing Wang, Kevin Diggs, Avanish Kulkarni, Kevin Steiger, Tai Vu, Vibha Venkataraman
2024 J jnl
Challenges of COVID-19 Case Forecasting in the US, 2020-2021.
PLoS Comput. Biol.
Velma K. Lopez, Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O'Dea, Madeline Adee, Turgay Ayer, Jagpreet Chhatwal, Ozden O. Dalgic, Mary A. Ladd, Benjamin P. Linas, Peter P. Mueller, Jade Xiao, Johannes Bracher, Alvaro J. Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Yuxin Huang, Dasuni Jayawardena, Abdul H. Kanji, Khoa Le, Anja Mühlemann, Jarad Niemi, Evan L. Ray, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W. Zorn, Sen Pei, Jeffrey Shaman, Teresa K. Yamana, Samuel R. Tarasewicz, Daniel J. Wilson, Sid Baccam, Heidi Gurung, Steve Stage, Brad Suchoski, Lei Gao, Zhiling Gu, Myungjin Kim, Xinyi Li, Guannan Wang, Lily Wang, Yueying Wang, Shan Yu, Lauren Gardner, Sonia Jindal, Maximilian Marshall, Kristen Nixon, Juan Dent, Alison L. Hill, Joshua Kaminsky, Elizabeth C. Lee, Joseph Chadi Lemaitre, Justin Lessler, Claire P. Smith, Shaun Truelove, Matt Kinsey, Luke C. Mullany, Kaitlin Rainwater-Lovett, Lauren Shin, Katharine Tallaksen, Shelby Wilson, Dean Karlen, Lauren A. Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Jiang Bian, Wei Cao, Zhifeng Gao, Juan M. Lavista Ferres, Chaozhuo Li, Tie-Yan Liu, Xing Xie, Shun Zhang, Shun Zheng, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana L. Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Robert Walraven, Jinghui Chen, Quanquan Gu, Lingxiao Wang, Pan Xu, Weitong Zhang, Difan Zou, Graham Casey Gibson, Daniel Sheldon, Ajitesh Srivastava, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Lijing Wang, Pragati V. Prasad, Jo W. Walker, Alexander E. Webber, Rachel B. Slayton, Matthew Biggerstaff, Nicholas G. Reich, Michael A. Johansson
2023 A* conf
Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts.
AAAI
Aniruddha Adiga, Gursharn Kaur, Lijing Wang, Benjamin Hurt, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe
2023 — conf
Two-Stage Fine-Tuning for Improved Bias and Variance for Large Pretrained Language Models.
ACL (1)
Lijing Wang, Yingya Li, Timothy Miller, Steven Bethard, Guergana Savova
2022 A* conf
CausalGNN: Causal-Based Graph Neural Networks for Spatio-Temporal Epidemic Forecasting.
AAAI
Lijing Wang, Aniruddha Adiga, Jiangzhuo Chen, Adam Sadilek, Srinivasan Venkatramanan, Madhav V. Marathe
2022 B conf
Enhancing COVID-19 Ensemble Forecasting Model Performance Using Auxiliary Data Sources.
IEEE Big Data
Aniruddha Adiga, Gursharn Kaur, Benjamin Hurt, Lijing Wang, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan L. Lewis, Madhav V. Marathe
2021 A* conf
All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting.
KDD
Aniruddha Adiga, Lijing Wang, Benjamin Hurt, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Bryan Leroy Lewis, Madhav V. Marathe
2021 A conf
Cohorting to Isolate Asymptomatic Spreaders: An Agent-Based Simulation Study on the Mumbai Suburban Railway.
AAMAS
Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav V. Marathe, Rajesh Sundaresan, Milind Tambe
2020 J jnl
Cohorting to isolate asymptomatic spreaders: An agent-based simulation study on the Mumbai Suburban Railway.
CoRR
Alok Talekar, Sharad Shriram, Nidhin K. Vaidhiyan, Gaurav Aggarwal, Jiangzhuo Chen, Srinivasan Venkatramanan, Lijing Wang, Aniruddha Adiga, Adam Sadilek, Ashish Tendulkar, Madhav V. Marathe, Rajesh Sundaresan, Milind Tambe
2020 A conf
Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction.
CIKM
Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning
2020 — conf
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting.
IEEE BigData
Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, Jiangzhuo Chen, Bryan L. Lewis, Madhav V. Marathe
2020 J jnl
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting.
CoRR
Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, Jiangzhuo Chen, Bryan L. Lewis, Madhav V. Marathe
2020 J jnl
TDEFSI: Theory Guided Deep Learning Based Epidemic Forecasting with Synthetic Information.
CoRR
Lijing Wang, Jiangzhuo Chen, Madhav V. Marathe
2020 J jnl
TDEFSI: Theory-guided Deep Learning-based Epidemic Forecasting with Synthetic Information.
ACM Trans. Spatial Algorithms Syst.
Lijing Wang, Jiangzhuo Chen, Madhav V. Marathe
2020 A* conf
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models.
NeurIPS
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Ahmed K. Farahat, Mahbubul Alam, Chetan Gupta, Jiangzhuo Chen, Madhav V. Marathe
2020 J jnl
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models.
CoRR
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Ahmed K. Farahat, Mahbubul Alam, Chetan Gupta, Jiangzhuo Chen, Madhav V. Marathe
2019 J jnl
A framework for discovering health disparities among cohorts in an influenza epidemic.
World Wide Web
Lijing Wang, Jiangzhuo Chen, Achla Marathe
2019 A* conf
DEFSI: Deep Learning Based Epidemic Forecasting with Synthetic Information.
AAAI
Lijing Wang, Jiangzhuo Chen, Madhav V. Marathe
2019 J jnl
Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction.
CoRR
Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning
2018 A* conf
Social Media based Simulation Models for Understanding Disease Dynamics.
IJCAI
Ting Hua, Chandan K. Reddy, Lei Zhang, Lijing Wang, Liang Zhao, Chang-Tien Lu, Naren Ramakrishnan
2017 — conf
PDGM: Percolation-based directed graph matching in social networks.
ICC
Lijing Wang, Jin-Hee Cho, Ing-Ray Chen, Jiangzhuo Chen