Matteo Chinazzi

19 papers A* 4Journal 15
YearRankTypeTitle / Venue / Authors
2025 J jnl
Epydemix: An open-source Python package for epidemic modeling with integrated approximate Bayesian calibration.
PLoS Comput. Biol.
Nicolò Gozzi, Matteo Chinazzi, Jessica T. Davis, Corrado Gioannini, Luca Rossi, Marco Ajelli, Nicola Perra, Alessandro Vespignani
2025 J jnl
SimulRAG: Simulator-based RAG for Grounding LLMs in Long-form Scientific QA.
CoRR
Haozhou Xu, Dongxia Wu, Matteo Chinazzi, Ruijia Niu, Rose Yu, Yi-An Ma
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
Deep Bayesian Active Learning for Accelerating Stochastic Simulation.
KDD
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2023 A* conf
Disentangled Multi-Fidelity Deep Bayesian Active Learning.
ICML
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yi-An Ma, Rose Yu
2023 J jnl
Disentangled Multi-Fidelity Deep Bayesian Active Learning.
CoRR
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yi-An Ma, Rose Yu
2022 J jnl
Anatomy of the first six months of COVID-19 vaccination campaign in Italy.
PLoS Comput. Biol.
Nicolò Gozzi, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana L. Pastore y Piontti, Marco Ajelli, Nicola Perra, Alessandro Vespignani
2022 A* conf
Multi-fidelity Hierarchical Neural Processes.
KDD
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2022 J jnl
Multi-fidelity Hierarchical Neural Processes.
CoRR
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
Accelerating Stochastic Simulation with Interactive Neural Processes.
CoRR
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave.
Nat.
Jessica T. Davis, Matteo Chinazzi, Nicola Perra, Kunpeng Mu, Ana L. Pastore y Piontti, Marco Ajelli, Natalie E. Dean, Corrado Gioannini, Maria Litvinova, Stefano Merler, Luca Rossi, Kaiyuan Sun, Xinyue Xiong, Ira M. Longini Jr., M. Elizabeth Halloran, Cécile Viboud, Alessandro Vespignani
2021 J jnl
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting.
CoRR
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches.
PLoS Comput. Biol.
Fred S. Lu, André T. Nguyen, Nicholas B. Link, Mathieu Molina, Jessica T. Davis, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Marc Lipsitch, Mauricio Santillana
2021 A* conf
Quantifying Uncertainty in Deep Spatiotemporal Forecasting.
KDD
Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu
2021 J jnl
Quantifying Uncertainty in Deep Spatiotemporal Forecasting.
CoRR
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
2020 J jnl
A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models.
CoRR
Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica T. Davis, Alessandro Vespignani, Mauricio Santillana
2020 J jnl
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks.
CoRR
Chintan Shah, Nima Dehmamy, Nicola Perra, Matteo Chinazzi, Albert-László Barabási, Alessandro Vespignani, Rose Yu
2019 J jnl
Mapping the physics research space: a machine learning approach.
EPJ Data Sci.
Matteo Chinazzi, Bruno Gonçalves, Qian Zhang, Alessandro Vespignani
2010 J jnl
Little Italy: An Agent-Based Approach to the Estimation of Contact Patterns- Fitting Predicted Matrices to Serological Data.
PLoS Comput. Biol.
Fabrizio Iozzi, Francesco Trusiano, Matteo Chinazzi, Francesco C. Billari, Emilio Zagheni, Stefano Merler, Marco Ajelli, Emanuele Del Fava, Piero Manfredi