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cs.LG2023
A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs
Sikun Yang, Hongyuan Zha
Continuously-observed event occurrences, often exhibit self- and mutually-exciting effects, which can be well modeled using temporal point processes. Beyond that, these event dynam…
cs.LG2023★ 1 cited
Learning Stochastic Dynamical Systems as an Implicit Regularization with Graph Neural Networks
Jin Guo, Ting Gao, Yufu Lan +3
Stochastic Gumbel graph networks are proposed to learn high-dimensional time series, where the observed dimensions are often spatially correlated. To that end, the observed randomn…