ZipIt! Merging Models from Different Tasks without Training

1 code implementation • 4 May 2023 • George Stoica, Daniel Bolya, Jakob Bjorner, Pratik Ramesh, Taylor Hearn, Judy Hoffman

While this works for models trained on the same task, we find that this fails to account for the differences in models trained on disjoint tasks.

Unified State Representation Learning under Data Augmentation

1 code implementation • 12 Sep 2022 • Taylor Hearn, Sravan Jayanthi, Sehoon Ha

The capacity for rapid domain adaptation is important to increasing the applicability of reinforcement learning (RL) to real world problems.

Data Augmentation Domain Adaptation +2