Subsequently, a graph-convolutional neural network-based surrogate learns parameter-dependent low-dimensional latent dynamics on the coarsest representation. Following surrogates are trained on residuals using finer resolutions, allowing for multiple surrogates with varying hardware requirements and increasing accuracy.doi:10.1007/s00466-024-...
Compared with the Koopman models previously used in biophysics and fluid dynamics, the introduction of graph convolutional neural networks enables parameter sharing between the atoms and an encoding of local environments that is invariant to permutation, rotation, and reflection. This symmetry facilitates ...
For example, in 2D or 3D, one can use convolutional networks42, as in image recognition; for sparse networks, graph neural networks are efficient43. Based on the VAN representation, we evaluate Eq. (2) by applying the operator \({e}^{\delta t{{\mathbb{W}}}_{s}}\) sequentially at...
Cross-domain inductive applications with unsupervised (dynamic) Graph Neural Networks (GNN): Leveraging Siamese GNN and energy-based PMI optimization Khushnood Abbas, Shi Dong, Alireza Abbasi, Yong Tang June 2025 Article 134632 select article Bayesian learning with Gaussian processes for low-dimensional ...
Graph neural network-based anomaly detection in multivariate time series. In: Proc. Thirty-Fifth AAAI Conference on Artificial Intelligence, 4027–4035 (AAAI Press, 2021). https://ojs.aaai.org/index.php/AAAI/article/view/16523. Hundman, K., Constantinou, V., Laporte, C., Colwell, I. &...
Mogonet inte- grates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification. Nature Communications, 12(1):1–13, 2021. 1, 2, 5, 8 [63] Weiran Wang, Raman Arora, Karen Livescu, and Jeff Bilmes. On deep ...
Simultaneous control of indoor air temperature and humidity for a chilled water based air conditioning system using neural networks 热度: a hybrid model for spatiotemporal forecasting of pm2.5 based on graph convolutional neural network and long short-term memory.[2019][sci total envi ...
Graph of singular value decay. (a): Singular value decay of solution snapshot, (b): Singular value decay of temporal snapshot for the first spatial basis vector. The Galerkin and LSPG space–time ROMs solve the Equation (62) with the target parameter ( μ 1 , μ 2 ) = ( 0.2 , ...
Kaliningraph treats string adjacency and graph adjacency as the same. To construct a graph, simply enumeratewalks. This can be done using a raw string, in which case unique characters will form the vertex set. Whitespace delimits walks: ...
EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networksdoi:10.1109/taffc.2018.2817622Tengfei SongWenming ZhengPeng SongZhen CuiIEEE