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Found 4 papers, 3 papers with code
Large Language Models to Enhance Bayesian Optimization
Bayesian optimization (BO) is a powerful approach for optimizing complex and expensive-to-evaluate black-box functions.
Multi-Class Deep SVDD: Anomaly Detection Approach in Astronomy with Distinct Inlier Categories
Our results demonstrate the efficacy of MCDSVDD in detecting anomalous sources while leveraging the presence of different inlier categories.
MPCC: Matching Priors and Conditionals for Clustering
Our experiments show that adding a learnable prior and augmenting the number of encoder updates improve the quality of the generated samples, obtaining an inception score of 9. 49 $\pm$ 0. 15 and improving the Fr\'echet inception distance over the state of the art by a 46. 9% in CIFAR10.
Matching Embeddings for Domain Adaptation
In this work we address the problem of transferring knowledge obtained from a vast annotated source domain to a low labeled target domain.
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