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81 |
Proximal Gradient Methods for General Smooth Graph Total Variation Model in Unsupervised Learning
Enthalten in Journal of scientific computing Bd. 93, 22.8.2022, Nr. 1, date:10.2022: 1-23
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82 |
Recognising small colour changes with unsupervised learning, comparison of methods
Enthalten in Advances in computational intelligence Bd. 4, 16.4.2024, Nr. 2, date:6.2024: 1-13
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83 |
Robustness of unsupervised methods for image surface-anomaly detection
Enthalten in Pattern analysis and applications Bd. 28, 3.5.2025, Nr. 2, date:6.2025: 1-12
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84 |
SMARTINI3 parametrization of multi-scale membrane models via unsupervised learning methods
Enthalten in Scientific reports Bd. 14, 28.10.2024, Nr. 1, date:12.2024: 1-20
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85 |
Supervised and Unsupervised Machine Learning Methods Applied for Enrolling Women in the Canadian Armed Forces
Enthalten in SN Computer Science Bd. 3, 26.4.2022, Nr. 3, date:5.2022: 1-15
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86 |
The relationship between clinical subtypes, prognosis, and treatment in ICU patients with acute cholangitis using unsupervised machine learning methods
Enthalten in BMC infectious diseases Bd. 25, 4.8.2025, Nr. 1, date:12.2025: 1-13
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87 |
Tracking the spatiotemporal evolution of groundwater chemistry in the Quaternary aquifer system of Debrecen area, Hungary: integration of classical and unsupervised learning methods
Enthalten in Environmental science and pollution research Bd. 32, 1.3.2025, Nr. 11, date:3.2025: 6884-6903
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88 |
Unsupervised 3D Ring Template Searching as an Ideas Generator for Scaffold Hopping: Use of the LAMDA, RigFit, and Field‐Based Similarity Search (FBSS) Methods.
Enthalten in ChemInform Bd. 37, 2006, Nr. 49: no-no. 1 S.
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89 |
Unsupervised Machine Learning Methods for Determining Special Points of the Polymerase Chain Reaction Fluorescence Accumulation Curve
Enthalten in Moskovskij gosudarstvennyj universitet im. M.V. Lomonosova: Moscow University physics bulletin Bd. 78, 17.1.2024, Nr. 1, date:12.2023: S169-S179
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90 |
Using unsupervised machine learning methods to cluster cardio-metabolic profile of the middle-aged and elderly Chinese with general and central obesity
Enthalten in BMC cardiovascular disorders Bd. 25, 27.10.2025, Nr. 1, date:12.2025: 1-13
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