Paper Reviews

Novel method for video prediction from a single frame by decomposing the scene into entities with location and appearance features, capturing ambiguities with a global latent variable.

Proposes multitask model to jointly learn semantic goal navigation and embodied question answering.

Investigates automatically generating curricula based on a variety of progress signals that are computed for each data sample.

Computer vision models trained on data obtained from head-mounted cameras on children performs better than data from adults.

Applies curriculum learning to a RL context to achieve policies.