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Modern data acquisition routinely produce massive amounts of event sequence data in various domains, such as social media, healthcare, and financial markets.
Self-attentive hawkes processes
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Learning social infectivity in sparse low-rank networks using multi-dimensional hawkes processes
Zhou, K · 2013
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Neural machine translation by jointly learning to align and translate
Bahdanau, D · 2014
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Chung, J · 2014
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Convolutional sequence to sequence learning
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Leskovec, J · 2014
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Discovering latent network structure in point process data
Linderman, S · 2014
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Hawkes processes in finance
Bacry, E · 2015
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Seismic: A self-exciting point process model for predicting tweet popularity
Zhao, Q · 2015
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Ba, J. L · 2016
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Recurrent marked temporal point processes: Embedding event history to vector
Du, N · 2016
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Deep residual learning for image recognition
He, K · 2016
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Yin, W · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J · 2018
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Learning temporal point processes via reinforcement learning
Li, S · 2018
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Self-attention with relative position representations
Shaw, P · 2018
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Supervised reinforcement learning with recurrent neural network for dynamic treatment recommendation
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Language models are unsupervised multitask learners
Radford, A · 2019
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