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Found 3 papers, 2 papers with code
Deep Bayesian Experimental Design for Quantum Many-Body Systems
Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain.
Unlocking the Power of Representations in Long-term Novelty-based Exploration
We introduce Robust Exploration via Clustering-based Online Density Estimation (RECODE), a non-parametric method for novelty-based exploration that estimates visitation counts for clusters of states based on their similarity in a chosen embedding space.
Renormalized Mutual Information for Artificial Scientific Discovery
We derive a well-defined renormalized version of mutual information that allows to estimate the dependence between continuous random variables in the important case when one is deterministically dependent on the other.
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