3 papers
cs.LG2026
What Does Flow Matching Bring To TD Learning?
Bhavya Agrawalla, Michal Nauman, Aviral Kumar
Recent work shows that flow matching can be effective for scalar Q-value function estimation in reinforcement learning (RL), but it remains unclear why or how this approach differs…
cs.LG2025
floq: Training Critics via Flow-Matching for Scaling Compute in Value-Based RL
Bhavya Agrawalla, Michal Nauman, Khush Agrawal +1
A hallmark of modern large-scale machine learning techniques is the use of training objectives that provide dense supervision to intermediate computations, such as teacher forcing…
cs.LG2025
Statistical Inference for Linear Functionals of Online Least-squares SGD when
Bhavya Agrawalla, Krishnakumar Balasubramanian, Promit Ghosal
Stochastic Gradient Descent (SGD) has become a cornerstone method in modern data science. However, deploying SGD in high-stakes applications necessitates rigorous quantification of…