191 citations · 425 across the 11 of their papers we have counts for
3 papers · 1 filter
Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces
Ziyad Sheebaelhamd, Konstantinos Zisis, Athina Nisioti +3
Multi-agent control problems constitute an interesting area of application for deep reinforcement learning models with continuous action spaces. Such real-world applications, howev…
Vanishing Curvature and the Power of Adaptive Methods in Randomly Initialized Deep Networks
Antonio Orvieto, Jonas Kohler, Dario Pavllo +2
This paper revisits the so-called vanishing gradient phenomenon, which commonly occurs in deep randomly initialized neural networks. Leveraging an in-depth analysis of neural chain…
Learning Generative Models of Textured 3D Meshes from Real-World Images
Dario Pavllo, Jonas Kohler, Thomas Hofmann +1
Recent advances in differentiable rendering have sparked an interest in learning generative models of textured 3D meshes from image collections. These models natively disentangle p…