This paper introduces Diffusion Policy, a new way of generating robot behavior by
representing a robot's visuomotor policy as a conditional denoising diffusion process. We …

A goal of artificial intelligence is to construct an agent that can solve a wide variety of tasks.
Recent progress in text-guided image synthesis has yielded models with an impressive …

The design of novel protein structures remains a challenge in protein engineering for
applications across biomedicine and chemistry. In this line of work, a diffusion model over …

We address the problem of generating realistic 3D motions of humans interacting with
objects in a scene. Our key idea is to create a neural interaction field attached to a specific …

We propose a new policy representation based on score-based diffusion models (SDMs).
We apply our new policy representation in the domain of Goal-Conditioned Imitation …

To make effective decisions in novel environments with long-horizon goals, it is crucial to
engage in hierarchical reasoning across spatial and temporal scales. This entails planning …

Self-supervised and language-supervised image models contain rich knowledge of the
world that is important for generalization. Many robotic tasks, however, require a detailed …

Modern successes of diffusion models in learning complex, high-dimensional data
distributions are attributed, in part, to their capability to construct diffusion processes with …

Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …

We present ChainedDiffuser, a policy architecture that unifies action keypose prediction and
trajectory diffusion generation for learning robot manipulation from demonstrations. Our …