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Found 5 papers, 1 papers with code
Epidemic Control Modeling using Parsimonious Models and Markov Decision Processes
The results show that the optimal policy acts swiftly to curb the epidemic in the first wave, thus avoiding the collapse of the healthcare system and the future costs of posterior outbreaks.
Designing MacPherson Suspension Architectures using Bayesian Optimization
We show that the proposed approach is general, scalable, and efficient, and that the novel convergence criteria can be implemented straightforwardly based on existing concepts and subroutines in popular Bayesian optimization software packages.
Causal Discovery in Knowledge Graphs by Exploiting Asymmetric Properties of Non-Gaussian Distributions
The proposed approach is based around the finding of the instantaneous causal structure of a non-experimental matrix using a non-Gaussian model, i. e; finding the causal ordering of the variables in a non-Gaussian setting.
Make Bipedal Robots Learn How to Imitate
In this paper we propose a method to train a bipedal robot to perform some basic movements with the help of imitation learning (IL) in which an instructor will perform the movement and the robot will try to mimic the instructor movement.
Generalized State-Feedback Controller Synthesis for Underactuated Systems through Bayesian Optimization
Underactuated systems pose the challenge of being able to control a plant whose degrees of freedom are not necessarily directly linked to an actuator or where such a relationship is not straightforward.
