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Found 2 papers, 1 papers with code
Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization
The problem can be framed as a global optimization problem where the objective is an expensive black-box function such that we can query large batches restricted with a limitation of a low number of rounds.
On the adaptation of recurrent neural networks for system identification
The system dynamics are then assumed to change, leading to an unacceptable degradation of the nominal model performance on the perturbed system.
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