4 citations · 8 across the 10 of their papers we have counts for
3 papers · 1 filter
IV-Posterior: Inverse Value Estimation for Interpretable Policy Certificates
Tatiana Lopez-Guevara, Michael Burke, Nicholas K. Taylor +1
Model-free reinforcement learning (RL) is a powerful tool to learn a broad range of robot skills and policies. However, a lack of policy interpretability can inhibit their successf…
Black-Box Saliency Map Generation Using Bayesian Optimisation
Mamuku Mokuwe, Michael Burke, Anna Sergeevna Bosman
Saliency maps are often used in computer vision to provide intuitive interpretations of what input regions a model has used to produce a specific prediction. A number of approaches…
Learning Structured Representations of Spatial and Interactive Dynamics for Trajectory Prediction in Crowded Scenes
Todor Davchev, Michael Burke, Subramanian Ramamoorthy
Context plays a significant role in the generation of motion for dynamic agents in interactive environments. This work proposes a modular method that utilises a learned model of th…