We fully discretize DreamerV2 and evaluate the discrete representation learned by the model.
Various model-based methods for extracting interpretable insights from discrete time series.
Capturing the agent’s behaviour through a policy representation that maps states of the world to actions.
Collection of capstone projects for final year CISC students
Dialogue Agents and Learning Constraints for SAT/CSPs