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Alessandro Corbetta

Showing results (1-10 of 13) with videos related to

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Mathematical Biosciences and Engineering : MBE|March 27, 2015
Parameter estimation of social forces in pedestrian dynamics models via a probabilistic methodAlessandro Corbetta, Adrian Muntean, Kiamars Vafayi
Chaos (Woodbury, N.Y.)|December 4, 2023
How neural networks learn to classify chaotic time seriesAlessandro Corbetta, Thomas Geert de Jong
Scientific Reports|July 17, 2020
Pedestrian orientation dynamics from high-fidelity measurementsJoris Willems, Alessandro Corbetta, Vlado Menkovski, et al.
Science Advances|March 18, 2021
Deep learning velocity signals allow quantifying turbulence intensityAlessandro Corbetta, Vlado Menkovski, Roberto Benzi, et al.
PNAS Nexus|January 30, 2023
Fluctuations in pedestrian dynamics routing choicesAlessandro Gabbana, Federico Toschi, Philip Ross, et al.
Scientific Reports|March 27, 2025
Discovering interaction mechanisms in crowds via deep generative surrogate experimentsKoen Minartz, Fleur Hendriks, Simon Martinus Koop, et al.
Plos One|October 29, 2020
Monitoring physical distancing for crowd management: Real-time trajectory and group analysisCaspar A S Pouw, Federico Toschi, Frank van Schadewijk, et al.
Physical Review. E|April 19, 2017
Fluctuations around mean walking behaviors in diluted pedestrian flowsAlessandro Corbetta, Chung-Min Lee, Roberto Benzi, et al.
The European Physical Journal. E, Soft Matter|March 6, 2023
Toward learning Lattice Boltzmann collision operatorsAlessandro Corbetta, Alessandro Gabbana, Vitaliy Gyrya, et al.
Physical Review. E|February 17, 2024
Stochastic fluctuations of diluted pedestrian dynamics along curved pathsGeert G M van der Vleuten, Federico Toschi, Wil Schilders, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
Mathematical Biosciences and Engineering : MBE|March 27, 2015
Parameter estimation of social forces in pedestrian dynamics models via a probabilistic methodAlessandro Corbetta, Adrian Muntean, Kiamars Vafayi
Chaos (Woodbury, N.Y.)|December 4, 2023
How neural networks learn to classify chaotic time seriesAlessandro Corbetta, Thomas Geert de Jong
Scientific Reports|July 17, 2020
Pedestrian orientation dynamics from high-fidelity measurementsJoris Willems, Alessandro Corbetta, Vlado Menkovski, et al.
Science Advances|March 18, 2021
Deep learning velocity signals allow quantifying turbulence intensityAlessandro Corbetta, Vlado Menkovski, Roberto Benzi, et al.
PNAS Nexus|January 30, 2023
Fluctuations in pedestrian dynamics routing choicesAlessandro Gabbana, Federico Toschi, Philip Ross, et al.
Scientific Reports|March 27, 2025
Discovering interaction mechanisms in crowds via deep generative surrogate experimentsKoen Minartz, Fleur Hendriks, Simon Martinus Koop, et al.
Plos One|October 29, 2020
Monitoring physical distancing for crowd management: Real-time trajectory and group analysisCaspar A S Pouw, Federico Toschi, Frank van Schadewijk, et al.
Physical Review. E|April 19, 2017
Fluctuations around mean walking behaviors in diluted pedestrian flowsAlessandro Corbetta, Chung-Min Lee, Roberto Benzi, et al.
The European Physical Journal. E, Soft Matter|March 6, 2023
Toward learning Lattice Boltzmann collision operatorsAlessandro Corbetta, Alessandro Gabbana, Vitaliy Gyrya, et al.
Physical Review. E|February 17, 2024
Stochastic fluctuations of diluted pedestrian dynamics along curved pathsGeert G M van der Vleuten, Federico Toschi, Wil Schilders, et al.
Pageof 2