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Pulkit Katdare

4 accepted papers

2023

Efficient Equivariant Transfer Learning from Pretrained Models

NeurIPS 2023poster

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 et al. (2022) propose group averaging (equitune) and optimization-based methods, respectively, over features from group-t…

2023

Marginalized Importance Sampling for Off-Environment Policy Evaluation

CoRL 2023poster

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 simulation requires a real-world deployment to assess their performance. This paper proposes a new approach to evaluate th…

Cited by 5SourceScholar
2022

Off Environment Evaluation Using Convex Risk Minimization

ICRA 2022poster

Applying reinforcement learning (RL) methods on robots typically involves training a policy in simulation and deploying it on a robot in the real world. Because of the model mismatch between the real world and the simulator, RL agents deployed in this manner tend to perform suboptimally. To tackle t…

Cited by 2SourcecodeScholar
2017

Trajectory tracking using motion primitives for the purcell's swimmer

IROS 2017poster

Locomotion at low Reynolds numbers is a topic of growing interest, spurred by its various engineering and medical applications. This paper presents a novel prototype and a locomotion algorithm for the 3-link planar Purcell's swimmer based on Lie algebraic notions. The kinematic model, based on Cox t…

Cited by 13SourceScholar