126 related articles for article (PubMed ID: 37393807)
41. Disease prediction with edge-variational graph convolutional networks.
Huang Y; Chung ACS
Med Image Anal; 2022 Apr; 77():102375. PubMed ID: 35144198
[TBL] [Abstract][Full Text] [Related]
42. A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning.
Mücke NT; Pandey P; Jain S; Bohté SM; Oosterlee CW
Sensors (Basel); 2023 Jul; 23(13):. PubMed ID: 37448028
[TBL] [Abstract][Full Text] [Related]
43. Research and Application of Ancient Chinese Pattern Restoration Based on Deep Convolutional Neural Network.
Fu X
Comput Intell Neurosci; 2021; 2021():2691346. PubMed ID: 34925485
[TBL] [Abstract][Full Text] [Related]
44. Remaining Useful Life Estimation for Engineered Systems Operating under Uncertainty with Causal GraphNets.
Mylonas C; Chatzi E
Sensors (Basel); 2021 Sep; 21(19):. PubMed ID: 34640645
[TBL] [Abstract][Full Text] [Related]
45. Contamination source identification in water distribution networks using convolutional neural network.
Sun L; Yan H; Xin K; Tao T
Environ Sci Pollut Res Int; 2019 Dec; 26(36):36786-36797. PubMed ID: 31745764
[TBL] [Abstract][Full Text] [Related]
46. Drug-target interaction predication via multi-channel graph neural networks.
Li Y; Qiao G; Wang K; Wang G
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34661237
[TBL] [Abstract][Full Text] [Related]
47. Utilizing artificial neural network to simulate and predict the hydraulic performance of free water surface constructed wetlands.
Guo C; Cui Y
J Environ Manage; 2022 Mar; 305():114334. PubMed ID: 34953224
[TBL] [Abstract][Full Text] [Related]
48. MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis.
Wen G; Cao P; Bao H; Yang W; Zheng T; Zaiane O
Comput Biol Med; 2022 Mar; 142():105239. PubMed ID: 35066446
[TBL] [Abstract][Full Text] [Related]
49. Water quality modeling in the dead end sections of drinking water distribution networks.
Abokifa AA; Yang YJ; Lo CS; Biswas P
Water Res; 2016 Feb; 89():107-17. PubMed ID: 26641015
[TBL] [Abstract][Full Text] [Related]
50. Assessing spatial connectivity effects on daily streamflow forecasting using Bayesian-based graph neural network.
Liu G; Ouyang S; Qin H; Liu S; Shen Q; Qu Y; Zheng Z; Sun H; Zhou J
Sci Total Environ; 2023 Jan; 855():158968. PubMed ID: 36162576
[TBL] [Abstract][Full Text] [Related]
51. Shall we upgrade one-dimensional secondary settler models used in WWTP simulators? - An assessment of model structure uncertainty and its propagation.
Plósz BG; De Clercq J; Nopens I; Benedetti L; Vanrolleghem PA
Water Sci Technol; 2011; 63(8):1726-38. PubMed ID: 21866774
[TBL] [Abstract][Full Text] [Related]
52. A complementary modelling approach to manage uncertainty of computationally expensive models.
Vojinovic Z
Water Sci Technol; 2007; 56(8):1-9. PubMed ID: 17978427
[TBL] [Abstract][Full Text] [Related]
53. [Hydraulic simulation and safety assessment of secondary water supply system with anti-negative pressure facility].
Wang HH; Liu SM; Jiang S; Meng FL; Bai L
Huan Jing Ke Xue; 2013 Jan; 34(1):163-8. PubMed ID: 23487933
[TBL] [Abstract][Full Text] [Related]
54. Complexity vs. simplicity: groundwater model ranking using information criteria.
Engelhardt I; De Aguinaga JG; Mikat H; Schüth C; Liedl R
Ground Water; 2014; 52(4):573-83. PubMed ID: 23750914
[TBL] [Abstract][Full Text] [Related]
55. Ground water model calibration using pilot points and regularization.
Doherty J
Ground Water; 2003; 41(2):170-7. PubMed ID: 12656283
[TBL] [Abstract][Full Text] [Related]
56. A unified deep semi-supervised graph learning scheme based on nodes re-weighting and manifold regularization.
Dornaika F; Bi J; Zhang C
Neural Netw; 2023 Jan; 158():188-196. PubMed ID: 36462365
[TBL] [Abstract][Full Text] [Related]
57. Identifying drug-target interactions based on graph convolutional network and deep neural network.
Zhao T; Hu Y; Valsdottir LR; Zang T; Peng J
Brief Bioinform; 2021 Mar; 22(2):2141-2150. PubMed ID: 32367110
[TBL] [Abstract][Full Text] [Related]
58. Reducing uncertainty in calibrating aquifer flow model with multiple scales of heterogeneity.
Zhang Y
Ground Water; 2014; 52(3):343-51. PubMed ID: 24749908
[TBL] [Abstract][Full Text] [Related]
59. Mapping ground water vulnerability to pesticide leaching with a process-based metamodel of EuroPEARL.
Tiktak A; Boesten JJ; van der Linden AM; Vanclooster M
J Environ Qual; 2006; 35(4):1213-26. PubMed ID: 16825441
[TBL] [Abstract][Full Text] [Related]
60. ATARI: A Graph Convolutional Neural Network Approach for Performance Prediction in Next-Generation WLANs.
Soto P; Camelo M; Mets K; Wilhelmi F; Góez D; Fletscher LA; Gaviria N; Hellinckx P; Botero JF; Latré S
Sensors (Basel); 2021 Jun; 21(13):. PubMed ID: 34202649
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]