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Found 4 papers, 2 papers with code
Domain Adaptation via Minimax Entropy for Real/Bogus Classification of Astronomical Alerts
Time domain astronomy is advancing towards the analysis of multiple massive datasets in real time, prompting the development of multi-stream machine learning models.
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.
Con$^{2}$DA: Simplifying Semi-supervised Domain Adaptation by Learning Consistent and Contrastive Feature Representations
We use different loss functions to enforce consistency between the feature representations of associated data pairs of samples.
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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