takes natural advantage of fully differentiable simulation, which is exploding in popularity and relevance

We thank the reviewers for their constructive feedback. NeurIPS, control of soft robots has seldom been addressed. We appreciate the reviewers' compliments that our submission is "an interesting piece of work that can have a good We believe concerns can be addressed within the review cycle with text improvements and additional experiments. CNNs can adequately learn over such inputs. We include a few new results below. The topheavy, unactuated head makes this a challenging control task. After 100 optimization iters., it runs 1.5 body lengths in 4 s . After 100 optimization iterations, it runs two body lengths in 4s . However, such an approach has never been demonstrated. Why a Latent Space Is Necessary ( R1). This approach doesn't scale: we tried feeding If the dynamics of the target trajectory are not explored initially, the observer and resulting optimization suffer. This issue is especially salient during design optimization, where system dynamics change. This is enough to bootstrap our learning. R1 wrote "of course the paper's focus is on multi-task learning for soft robotics.