6 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 6 cited
ZipIt! Merging Models from Different Tasks without Training
George Stoica, Daniel Bolya, Jakob Bjorner +3
Typical deep visual recognition models are capable of performing the one task they were trained on. In this paper, we tackle the extremely difficult problem of combining distinct m…
cs.LG2022
Unified State Representation Learning under Data Augmentation
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. Generalization of RL agents is critical…