57 citations · 61 across the 4 of their papers we have counts for
4 papers
Trojans in Artificial Intelligence (TrojAI) Final Report
Kristopher W. Reese, Taylor Kulp-McDowall, Michael Majurski +68
The Intelligence Advanced Research Projects Activity (IARPA) launched the TrojAI program to confront an emerging vulnerability in modern artificial intelligence: the threat of AI T…
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-Bénard convection
Joel Vasanth, Jean Rabault, Francisco Alcántara-Ávila +2
Deep reinforcement learning (DRL) has found application in numerous use-cases pertaining to flow control. Multi-agent RL (MARL), a variant of DRL, has shown to be more effective th…
Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality
Joongoo Jeon, Jean Rabault, Joel Vasanth +3
Flow control is key to maximize energy efficiency in a wide range of applications. However, traditional flow-control methods face significant challenges in addressing non-linear sy…
Effective control of two-dimensional Rayleigh--Bénard convection: invariant multi-agent reinforcement learning is all you need
Colin Vignon, Jean Rabault, Joel Vasanth +3
Rayleigh-Bénard convection (RBC) is a recurrent phenomenon in several industrial and geoscience flows and a well-studied system from a fundamental fluid-mechanics viewpoint. Howeve…