17 citations · 31 across the 9 of their papers we have counts for
11 papers
Advantage-Driven Explicit Memory for Social Navigation
Yeonsoo Park, Mattia Racca, Guillaume Bono +4
Robot policies are predominantly learned with classical parametric variants of imitation learning or RL, where training stores the agent's behavior exclusively in the policy's netw…
A scalar per patch from pre-trained ViTs enables fast moving navigation in the real world
Steeven Janny, Leonid Antsfeld, Christian Wolf
Trained policies for real-world robotics rely on computer vision components, typically in the form of pre-trained visual encoders. These encoders are an essential component and it…
Reasoning in visual navigation of end-to-end trained agents: a dynamical systems approach
Steeven Janny, Hervé Poirier, Leonid Antsfeld +6
Progress in Embodied AI has made it possible for end-to-end-trained agents to navigate in photo-realistic environments with high-level reasoning and zero-shot or language-condition…
Space and Time Continuous Physics Simulation From Partial Observations
Janny Steeven, Nadri Madiha, Digne Julie +1
Modern techniques for physical simulations rely on numerical schemes and mesh-refinement methods to address trade-offs between precision and complexity, but these handcrafted solut…
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…
Learning Reduced Nonlinear State-Space Models: an Output-Error Based Canonical Approach
Steeven Janny, Quentin Possamai, Laurent Bako +2
The identification of a nonlinear dynamic model is an open topic in control theory, especially from sparse input-output measurements. A fundamental challenge of this problem is tha…
Learning to estimate UAV created turbulence from scene structure observed by onboard cameras
Quentin Possamaï, Steeven Janny, Madiha Nadri +2
Controlling UAV flights precisely requires a realistic dynamic model and accurate state estimates from onboard sensors like UAV, GPS and visual observations. Obtaining a precise dy…
MoCap-less Quantitative Evaluation of Ego-Pose Estimation Without Ground Truth Measurements
Quentin Possamaï, Steeven Janny, Guillaume Bono +3
The emergence of data-driven approaches for control and planning in robotics have highlighted the need for developing experimental robotic platforms for data collection. However, t…
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space
Steeven Janny, Fabien Baradel, Natalia Neverova +3
Learning causal relationships in high-dimensional data (images, videos) is a hard task, as they are often defined on low dimensional manifolds and must be extracted from complex si…
Deep KKL: Data-driven Output Prediction for Non-Linear Systems
Steeven Janny, Vincent Andrieu, Madiha Nadri +1
We address the problem of output prediction, ie. designing a model for autonomous nonlinear systems capable of forecasting their future observations. We first define a general fram…
Attended Temperature Scaling: A Practical Approach for Calibrating Deep Neural Networks
Azadeh Sadat Mozafari, Hugo Siqueira Gomes, Wilson Leão +2
Recently, Deep Neural Networks (DNNs) have been achieving impressive results on wide range of tasks. However, they suffer from being well-calibrated. In decision-making application…