metadata
title: Sample-Efficient Imitation
emoji: 🎯
colorFrom: green
colorTo: blue
sdk: static
pinned: true
license: mit
short_description: Does regularization buy sample-efficiency? (PushT)
Sample-Efficient Imitation — live results
Does aggressive regularization buy sample-efficiency for imitation-learning policies? Diffusion Policy on PushT, trained & evaluated on AMD ROCm (Radeon AI PRO R9700).
The page (index.html) shows the policy solving the task (real eval rollouts) and the
data-efficiency comparison. Code: https://github.com/enyolanev-bit/sample-efficient-imitation