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Jean Rabault

Showing results (1-10 of 9) with videos related to

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Physical Review Letters|February 6, 2019
Curving to Fly: Synthetic Adaptation Unveils Optimal Flight Performance of Whirling FruitsJean Rabault, Richard A Fauli, Andreas Carlson
Physical Review. E|September 11, 2019
Effect of wing fold angles on the terminal descent velocity of double-winged autorotating seeds, fruits, and other diasporesRichard A Fauli, Jean Rabault, Andreas Carlson
The European Physical Journal. E, Soft Matter|April 11, 2023
Deep reinforcement learning for turbulent drag reduction in channel flowsLuca Guastoni, Jean Rabault, Philipp Schlatter, et al.
Flow, Turbulence and Combustion|October 13, 2025
Multi-agent Reinforcement Learning for the Control of Three-Dimensional Rayleigh-Bénard ConvectionJoel Vasanth, Jean Rabault, Francisco Alcántara-Ávila, et al.
Nature Communications|February 6, 2025
Deep reinforcement learning for active flow control in a turbulent separation bubbleBernat Font, Francisco Alcántara-Ávila, Jean Rabault, et al.
Communications Engineering|June 18, 2025
Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learningPol Suárez, Francisco Alcántara-Ávila, Jean Rabault, et al.
Scientific Data|September 30, 2025
Svalbard Marginal Ice Zone 2024: A distributed network of temperature, waves, and sea ice drift observationsMalte Müller, Jean Rabault, Chiara de Geeter, et al.
Scientific Data|May 3, 2023
A dataset of direct observations of sea ice drift and waves in iceJean Rabault, Malte Müller, Joey Voermans, et al.
Scientific Data|December 21, 2024
A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023Jean Rabault, Catherine Taelman, Martina Idžanović, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Physical Review Letters|February 6, 2019
Curving to Fly: Synthetic Adaptation Unveils Optimal Flight Performance of Whirling FruitsJean Rabault, Richard A Fauli, Andreas Carlson
Physical Review. E|September 11, 2019
Effect of wing fold angles on the terminal descent velocity of double-winged autorotating seeds, fruits, and other diasporesRichard A Fauli, Jean Rabault, Andreas Carlson
The European Physical Journal. E, Soft Matter|April 11, 2023
Deep reinforcement learning for turbulent drag reduction in channel flowsLuca Guastoni, Jean Rabault, Philipp Schlatter, et al.
Flow, Turbulence and Combustion|October 13, 2025
Multi-agent Reinforcement Learning for the Control of Three-Dimensional Rayleigh-Bénard ConvectionJoel Vasanth, Jean Rabault, Francisco Alcántara-Ávila, et al.
Nature Communications|February 6, 2025
Deep reinforcement learning for active flow control in a turbulent separation bubbleBernat Font, Francisco Alcántara-Ávila, Jean Rabault, et al.
Communications Engineering|June 18, 2025
Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learningPol Suárez, Francisco Alcántara-Ávila, Jean Rabault, et al.
Scientific Data|September 30, 2025
Svalbard Marginal Ice Zone 2024: A distributed network of temperature, waves, and sea ice drift observationsMalte Müller, Jean Rabault, Chiara de Geeter, et al.
Scientific Data|May 3, 2023
A dataset of direct observations of sea ice drift and waves in iceJean Rabault, Malte Müller, Joey Voermans, et al.
Scientific Data|December 21, 2024
A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023Jean Rabault, Catherine Taelman, Martina Idžanović, et al.
Pageof 1