2 papers
cs.LG2025
FAST-Q: Fast-track Exploration with Adversarially Balanced State Representations for Counterfactual Action Estimation in Offline Reinforcement Learning
Pulkit Agrawal, Rukma Talwadker, Aditya Pareek +1
Recent advancements in state-of-the-art (SOTA) offline reinforcement learning (RL) have primarily focused on addressing function approximation errors, which contribute to the overe…
cs.LG2025
Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay
Hussain Jagirdar, Rukma Talwadker, Aditya Pareek +2
Multi-variate Time Series (MTS) forecasting has made large strides (with very negligible errors) through recent advancements in neural networks, e.g., Transformers. However, in cri…