no code implementations • 29 Mar 2024 • Luke Rowe, Roger Girgis, Anthony Gosselin, Bruno Carrez, Florian Golemo, Felix Heide, Liam Paull, Christopher Pal
With this dataset, we train a return-conditioned multi-agent behaviour model that allows for fine-grained manipulation of agent behaviours by modifying the desired returns for the various reward components.
no code implementations • CVPR 2023 • Luke Rowe, Martin Ethier, Eli-Henry Dykhne, Krzysztof Czarnecki
In this work, we address the problem of generating a set of scene-level, or joint, future trajectory predictions in multi-agent driving scenarios.
no code implementations • 5 Oct 2022 • Luke Rowe, Benjamin Thérien, Krzysztof Czarnecki, Hongyang Zhang
In adversarial machine learning, the popular $\ell_\infty$ threat model has been the focus of much previous work.
no code implementations • 28 Sep 2022 • Chengjie Huang, Van Duong Nguyen, Vahdat Abdelzad, Christopher Gus Mannes, Luke Rowe, Benjamin Therien, Rick Salay, Krzysztof Czarnecki
Detecting OOD inputs is challenging and essential for the safe deployment of models.