(2016) used this graph neural network to learn the communication between multiple agents to solve multiple tasks like traffic control. Syntactic Graph Convolutional Networks of Marcheggiani & Titov (2017). The authors proposed the following transfer function: hiℓ+1=fS-GCNℓ({hjℓ:j→i...
目录Abstract Introduction & Methodology 物理图 (physical graph) 流量相似性图 (similarity graph) 流量相关性图 (correlation graph) Model Graph Convolution Gated Recurrent Unit (GC-GRU) Fully-Connected Gated Recurre...实体-关系联合抽取:Table Filling Multi-Task Recurrent Neural Network for Joint Entity ...
Once the forward pass is completed, this graph is evaluated in the backward pass to compute the gradients. To build the backward pass, we used the concept of free energy as presented in (9). Under the gated RBM, the probability of observing a configuration of output units 𝐲y given the...