Abstract: Highlights•We develop CLDNE to derive generalized representations for dynamic networks.•We propose a streaming graph auto-encoder in CLDNE to learn global patterns.•We design an experience replay buffer to replay high-order historical topology.•We highlight static historical features using a knowledge distillation module.
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