4 citations · 4 across the 5 of their papers we have counts for
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cs.LG2023
Marginalized Importance Sampling for Off-Environment Policy Evaluation
Pulkit Katdare, Nan Jiang, Katherine Driggs-Campbell
Reinforcement Learning (RL) methods are typically sample-inefficient, making it challenging to train and deploy RL-policies in real world robots. Even a robust policy trained in si…
cs.LG2023
Efficient Equivariant Transfer Learning from Pretrained Models
Sourya Basu, Pulkit Katdare, Prasanna Sattigeri +4
Efficient transfer learning algorithms are key to the success of foundation models on diverse downstream tasks even with limited data. Recent works of Basu et al. (2023) and Kaba e…