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Found 5 papers, 1 papers with code
Amortizing intractable inference in diffusion models for vision, language, and control
Diffusion models have emerged as effective distribution estimators in vision, language, and reinforcement learning, but their use as priors in downstream tasks poses an intractable posterior inference problem.
CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning
In this work, we take an alternative approach and propose CtRL-Sim, a method that leverages return-conditioned offline reinforcement learning to efficiently generate reactive and controllable traffic agents.
FJMP: Factorized Joint Multi-Agent Motion Prediction over Learned Directed Acyclic Interaction Graphs
In this work, we address the problem of generating a set of scene-level, or joint, future trajectory predictions in multi-agent driving scenarios.
A Closer Look at Robustness to L-infinity and Spatial Perturbations and their Composition
In adversarial machine learning, the popular $\ell_\infty$ threat model has been the focus of much previous work.
Out-of-Distribution Detection for LiDAR-based 3D Object Detection
Detecting OOD inputs is challenging and essential for the safe deployment of models.
