Few-Shot In-Context Imitation Learning via Implicit Graph Alignment

no code implementations • 18 Oct 2023 • Vitalis Vosylius, Edward Johns

Consequently, we show that this conditioning allows for in-context learning, where a robot can perform a task on a set of new objects immediately after the demonstrations, without any prior knowledge about the object class or any further training.

Few-Shot Learning Imitation Learning +1

Where To Start? Transferring Simple Skills to Complex Environments

no code implementations • 12 Dec 2022 • Vitalis Vosylius, Edward Johns

Robot learning provides a number of ways to teach robots simple skills, such as grasping.

DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics

no code implementations • 5 Oct 2022 • Ivan Kapelyukh, Vitalis Vosylius, Edward Johns

We introduce the first work to explore web-scale diffusion models for robotics.

Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface

1 code implementation • 13 Aug 2020 • Vitalis Vosylius, Andy Wang, Cemlyn Waters, Alexey Zakharov, Francis Ward, Loic Le Folgoc, John Cupitt, Antonios Makropoulos, Andreas Schuh, Daniel Rueckert, Amir Alansary

In this paper, we propose a novel approach to predict the post-menstrual age (PA) at scan, using techniques from geometric deep learning, based on the neonatal white matter cortical surface.