6 citations · 26 across the 14 of their papers we have counts for
4 papers · 1 filter
Learning whom to trust in navigation: dynamically switching between classical and neural planning
Sombit Dey, Assem Sadek, Gianluca Monaci +2
Navigation of terrestrial robots is typically addressed either with localization and mapping (SLAM) followed by classical planning on the dynamically created maps, or by machine le…
Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction
Guillaume Bono, Leonid Antsfeld, Assem Sadek +2
Agents navigating in 3D environments require some form of memory, which should hold a compact and actionable representation of the history of observations useful for decision takin…
AutoNeRF: Training Implicit Scene Representations with Autonomous Agents
Pierre Marza, Laetitia Matignon, Olivier Simonin +3
Implicit representations such as Neural Radiance Fields (NeRF) have been shown to be very effective at novel view synthesis. However, these models typically require manual and care…
Eagle: Large-Scale Learning of Turbulent Fluid Dynamics with Mesh Transformers
Steeven Janny, Aurélien Béneteau, Madiha Nadri +3
Estimating fluid dynamics is classically done through the simulation and integration of numerical models solving the Navier-Stokes equations, which is computationally complex and t…