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Deep reinforcement learning for optimal experimental design in biology.
Neythen J. Treloar
Nathan Braniff
Brian P. Ingalls
Chris P. Barnes
Published in:
PLoS Comput. Biol. (2022)
Keyphrases
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experimental design
reinforcement learning
stochastic dynamic programming
active learning
approximate dynamic programming
empirical studies
experimental designs
class imbalance
optimal solution
worst case
sample size
control policy
continuous state
naive bayes
machine learning
user interface
feature selection