8 citations · 12 across the 5 of their papers we have counts for
5 papers
Difference-Aware Retrieval Policies for Imitation Learning
Quinn Pfeifer, Ethan Pronovost, Paarth Shah +3
Parametric imitation learning via behavior cloning can suffer from poor generalization to out-of-distribution states due to compounding errors during deployment. We show that reusi…
The Geometry of Learning to Avoid Interventions
Ethan Pronovost, Khimya Khetarpal, Siddhartha Srinivasa
Human interventions are a common source of supervision in autonomous systems during deployment. Many existing approaches are based on avoiding interventions, yet the consequences o…
Linear Memory SE(2) Invariant Attention
Ethan Pronovost, Neha Boloor, Peter Schleede +3
Processing spatial data is a key component in many learning tasks for autonomous driving such as motion forecasting, multi-agent simulation, and planning. Prior works have demonstr…
Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
Ethan Pronovost, Meghana Reddy Ganesina, Noureldin Hendy +4
Automated creation of synthetic traffic scenarios is a key part of validating the safety of autonomous vehicles (AVs). In this paper, we propose Scenario Diffusion, a novel diffusi…
Generating Driving Scenes with Diffusion
Ethan Pronovost, Kai Wang, Nick Roy
In this paper we describe a learned method of traffic scene generation designed to simulate the output of the perception system of a self-driving car. In our "Scene Diffusion" syst…