Search Results for author:
Found 2 papers, 1 papers with code
Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery
In this work, we propose a novel Gradient-based Intervention Targeting method, abbreviated GIT, that 'trusts' the gradient estimator of a gradient-based causal discovery framework to provide signals for the intervention acquisition function.
Continuous Control With Ensemble Deep Deterministic Policy Gradients
The growth of deep reinforcement learning (RL) has brought multiple exciting tools and methods to the field.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
