We are implementing differentiable models of robot manipulators, which allows us to learn typically assumed to be known models of robots for control and motion planning.

A non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification

Collection of algorithms to learn loss and reward functions via gradient-based bi-level optimization.

higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual training steps.

Hydra is a framework for elegantly configuring complex applications