Matteo Chinazzi

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 15

Top Topics

Machine Learning

Stochastic Simulation

Spatiotemporal Databases

Severe Acute Respiratory Syndrome

Top Venues

PLoS Comput. Biol.

Publications

Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu
Disentangled Multi-Fidelity Deep Bayesian Active Learning. ICML (2023)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Deep Bayesian Active Learning for Accelerating Stochastic Simulation. KDD (2023)
Dongxia Wu, Ruijia Niu, Matteo Chinazzi, Yian Ma, Rose Yu
Disentangled Multi-Fidelity Deep Bayesian Active Learning. CoRR (2023)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Multi-fidelity Hierarchical Neural Processes. CoRR (2022)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Multi-fidelity Hierarchical Neural Processes. KDD (2022)
Nicolò Gozzi, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana L. Pastore y Piontti, Marco Ajelli, Nicola Perra, Alessandro Vespignani
Anatomy of the first six months of COVID-19 vaccination campaign in Italy. PLoS Comput. Biol. 18 (5) (2022)
Dongxia Wu, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Accelerating Stochastic Simulation with Interactive Neural Processes. CoRR (2021)
Dongxia Wu, Liyao Gao, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Yi-An Ma, Rose Yu
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. KDD (2021)
Fred S. Lu, André T. Nguyen, Nicholas B. Link, Mathieu Molina, Jessica T. Davis, Matteo Chinazzi, Xinyue Xiong, Alessandro Vespignani, Marc Lipsitch, Mauricio Santillana
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. 17 (6) (2021)
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yi-An Ma, Rose Yu
Quantifying Uncertainty in Deep Spatiotemporal Forecasting. CoRR (2021)
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
Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave. Nat. 600 (7887) (2021)
Dongxia Wu, Liyao Gao, Xinyue Xiong, Matteo Chinazzi, Alessandro Vespignani, Yian Ma, Rose Yu
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting. CoRR (2021)
Chintan Shah, Nima Dehmamy, Nicola Perra, Matteo Chinazzi, Albert-László Barabási, Alessandro Vespignani, Rose Yu
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks. CoRR (2020)
Dianbo Liu, Leonardo Clemente, Canelle Poirier, Xiyu Ding, Matteo Chinazzi, Jessica T. Davis, Alessandro Vespignani, Mauricio Santillana
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 (2020)
Matteo Chinazzi, Bruno Gonçalves, Qian Zhang, Alessandro Vespignani
Mapping the physics research space: a machine learning approach. EPJ Data Sci. 8 (1) (2019)
Fabrizio Iozzi, Francesco Trusiano, Matteo Chinazzi, Francesco C. Billari, Emilio Zagheni, Stefano Merler, Marco Ajelli, Emanuele Del Fava, Piero Manfredi
Little Italy: An Agent-Based Approach to the Estimation of Contact Patterns- Fitting Predicted Matrices to Serological Data. PLoS Comput. Biol. 6 (12) (2010)