Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Novati, Guido"'
Autor:
Tudosiu, Petru-Daniel, Pinaya, Walter Hugo Lopez, Graham, Mark S., Borges, Pedro, Fernandez, Virginia, Yang, Dai, Appleyard, Jeremy, Novati, Guido, Mehra, Disha, Vella, Mike, Nachev, Parashkev, Ourselin, Sebastien, Cardoso, Jorge
Human anatomy, morphology, and associated diseases can be studied using medical imaging data. However, access to medical imaging data is restricted by governance and privacy concerns, data ownership, and the cost of acquisition, thus limiting our abi
Externí odkaz:
http://arxiv.org/abs/2209.03177
Publikováno v:
Phys. Rev. Fluids 6, 093101 (2021)
Swimming organisms can escape their predators by creating and harnessing unsteady flow fields through their body motions. Stochastic optimization and flow simulations have identified escape patterns that are consistent with those observed in natural
Externí odkaz:
http://arxiv.org/abs/2105.00771
Efficient point-to-point navigation in the presence of a background flow field is important for robotic applications such as ocean surveying. In such applications, robots may only have knowledge of their immediate surroundings or be faced with time-v
Externí odkaz:
http://arxiv.org/abs/2102.10536
We propose Improved Memories Learning (IMeL), a novel algorithm that turns reinforcement learning (RL) into a supervised learning (SL) problem and delimits the role of neural networks (NN) to interpolation. IMeL consists of two components. The first
Externí odkaz:
http://arxiv.org/abs/2008.10433
The modeling of turbulent flows is critical to scientific and engineering problems ranging from aircraft design to weather forecasting and climate prediction. Over the last sixty years numerous turbulence models have been proposed, largely based on p
Externí odkaz:
http://arxiv.org/abs/2005.09023
Autor:
Weber, Pascal, Arampatzis, Georgios, Novati, Guido, Verma, Siddhartha, Papadimitriou, Costas, Koumoutsakos, Petros
Publikováno v:
Biomimetics 2020, 5(1), 10
Fish schooling implies an awareness of the swimmers for their companions. In flow mediated environments, in addition to visual cues, pressure and shear sensors on the fish body are critical for providing quantitative information that assists the quan
Externí odkaz:
http://arxiv.org/abs/1910.09937
Autor:
Novati, Guido, Koumoutsakos, Petros
Experience replay (ER) is a fundamental component of off-policy deep reinforcement learning (RL). ER recalls experiences from past iterations to compute gradient estimates for the current policy, increasing data-efficiency. However, the accuracy of s
Externí odkaz:
http://arxiv.org/abs/1807.05827
Controlled gliding is one of the most energetically efficient modes of transportation for natural and human powered fliers. Here we demonstrate that gliding and landing strategies with different optimality criteria can be identified through deep rein
Externí odkaz:
http://arxiv.org/abs/1807.03671
Fish in schooling formations navigate complex flow-fields replete with mechanical energy in the vortex wakes of their companions. Their schooling behaviour has been associated with evolutionary advantages including collective energy savings. How fish
Externí odkaz:
http://arxiv.org/abs/1802.02674
The distribution of forces on the surface of complex, deforming geometries is an invaluable output of flow simulations. One particular example of such geometries involves self-propelled swimmers. Surface forces can provide significant information abo
Externí odkaz:
http://arxiv.org/abs/1610.04398