64 citations · 82 across the 5 of their papers we have counts for
5 papers
DiWA: Diffusion Policy Adaptation with World Models
Akshay L Chandra, Iman Nematollahi, Chenguang Huang +3
Fine-tuning diffusion policies with reinforcement learning (RL) presents significant challenges. The long denoising sequence for each action prediction impedes effective reward pro…
LUMOS: Language-Conditioned Imitation Learning with World Models
Iman Nematollahi, Branton DeMoss, Akshay L Chandra +3
We introduce LUMOS, a language-conditioned multi-task imitation learning framework for robotics. LUMOS learns skills by practicing them over many long-horizon rollouts in the laten…
On Initial Pools for Deep Active Learning
Akshay L Chandra, Sai Vikas Desai, Chaitanya Devaguptapu +1
Active Learning (AL) techniques aim to minimize the training data required to train a model for a given task. Pool-based AL techniques start with a small initial labeled pool and t…
Active Learning with Point Supervision for Cost-Effective Panicle Detection in Cereal Crops
Akshay L Chandra, Sai Vikas Desai, Vineeth N Balasubramanian +2
Panicle density of cereal crops such as wheat and sorghum is one of the main components for plant breeders and agronomists in understanding the yield of their crops. To phenotype t…
An Adaptive Supervision Framework for Active Learning in Object Detection
Sai Vikas Desai, Akshay L Chandra, Wei Guo +2
Active learning approaches in computer vision generally involve querying strong labels for data. However, previous works have shown that weak supervision can be effective in traini…