Search Results for author:
Found 3 papers, 1 papers with code
Deep Learning Based Object Tracking in Walking Droplet and Granular Intruder Experiments
We present a deep-learning based tracking objects of interest in walking droplet and granular intruder experiments.
Algorithms for Adaptive Experiments that Trade-off Statistical Analysis with Reward: Combining Uniform Random Assignment and Reward Maximization
TS-PostDiff takes a Bayesian approach to mixing TS and Uniform Random (UR): the probability a participant is assigned using UR allocation is the posterior probability that the difference between two arms is 'small' (below a certain threshold), allowing for more UR exploration when there is little or no reward to be gained.
Efficient Inference Without Trading-off Regret in Bandits: An Allocation Probability Test for Thompson Sampling
Increasing power in such small pilot experiments, without limiting the adaptive nature of the algorithm, can allow promising interventions to reach a larger experimental phase.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
