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Source:
Yao, Y, Dai, S, Li, Y, Chen, L, Li, D, Gao, Y & Li, T 2024, 'A Demonstration of TENDS : Time Series Management System based on Model
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Source:
Yao, Y, Li, D, Jie, H, Chen, L, Li, T, Chen, J, Wang, J, Li, F & Gao, Y 2023, 'SimpleTS : An Efficient and Universal Model Selection
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Subjects: electric vehicle; loss model; lifetime
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Source:
Xia, H, Zhang, Y, Zhou, D, Chen, M, Lai, W, Wei, Y & Wang, H 2022, Impact of Loss Model Selection on Power Semiconductor Lifetime
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Source:
Rasmussen, C B & Moeslund, T B 2020, 'Evaluation of Model Selection for Kernel Fragment Recognition in Corn Silage', Paper presented at
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Subjects: Decentralised plan comparison; Head and neck proton treatment; Model selection
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Source:
Hansen, C R, Jensen, K, Smulders, B, Holm, A I S, Samsøe, E, Nielsen, M S, Sibolt, P, Skyt, P, Elstrøm, U V, Nielsen, C P, Johansen, J, Zukauskaite, R, Eriksen, J G, Farhadi, M, Andersen, M,
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Subjects: Multi-pitch estimation; model selection; multi-channel pitch estimation
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Source:
Hansen, M W, Jensen, J R & Christensen, M G 2019, 'Estimation of Fundamental Frequencies in Stereophonic Music Mixtures', IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 27, no.
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Subjects: Forecast evaluation; Model selection; Renewable energy
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Source:
Ulbricht, R, Donker, H, Hartmann, C, Hahmann, M & Lehner, W 2016, 'Challenges for context-driven time series forecasting', Journal of Data and Information Quality, vol. 7, no. 1-2, 5.
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Subjects: Wireless communication; Training; Power system reliability
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Source:
Angjelichinoski, M, Trillingsgaard, K F & Popovski, P 2019, 'A Statistical Learning Approach to Ultra-Reliable Low Latency Communication', IEEE Transactions on Communications, vol. 67, no. 7, 8673783,
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Source:
Lachi, V, Ferrini, F, Longa, A, Lepri, B, Passerini, A & Jaeger, M 2025, Bridging Theory and Practice in Link Representation with Graph Neural Networks. in The Thirty-ninth Annual Conference on Neural
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