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AuDoLab: Automatic document labelling and classification for extremely unbalanced data.

, , , , , , and . J. Open Source Softw., 6 (66): 3719 (2021)

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Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean., , , and . CoRR, (2023)Structural Neural Additive Models: Enhanced Interpretable Machine Learning., , and . CoRR, (2023)Community-Detection via Hashtag-Graphs for Semi-Supervised NMF Topic Models., , , and . CoRR, (2021)Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data., , , , , , and . Comput. Stat., 38 (2): 647-674 (June 2023)AuDoLab: Automatic document labelling and classification for extremely unbalanced data., , , , , , and . J. Open Source Softw., 6 (66): 3719 (2021)Topics in the Haystack: Extracting and Evaluating Topics beyond Coherence., , , , and . CoRR, (2023)GPTopic: Dynamic and Interactive Topic Representations., , , , and . CoRR, (2024)Coherence based Document Clustering., , , and . ICSC, page 9-16. IEEE, (2023)Human in the loop: How to effectively create coherent topics by manually labeling only a few documents per class., , and . CoRR, (2022)Probabilistic Topic Modelling with Transformer Representations., , , , and . CoRR, (2024)