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Point processes are becoming very popular in modeling asynchronous sequential data due to their sound mathematical foundation and strength in modeling a variety of real-world phenomena.
Spectra of some self-exciting and mutually exciting point processes
Alan G Hawkes · 1971
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A self-correcting point process
Valerie Isham and Mark Westcott · 1979
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On lewis’ simulation method for point processes
Yosihiko Ogata · 1981
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Poisson processes
John Frank Charles Kingman · 1993
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An introduction to the theory of point processes
DJ Daley and D Vere-Jones · 2003
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Survival and event history analysis: a process point of view
Odd Aalen, Ornulf Borgan, and Hakon Gjessing · 2008
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Optimal transport: old and new
Cédric Villani · 2008
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A new metric between distributions of point processes
Dominic Schuhmacher and Aihua Xia · 2008
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Discovering latent network structure in point process data
Scott W Linderman and Ryan P Adams · 2014
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Path to purchase: A mutually exciting point process model for online advertising and conversion
Lizhen Xu, Jason A Duan, and Andrew Whinston · 2014
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Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Wenzhao Lian, Ricardo Henao, Vinayak Rao, Joseph E Lucas, and Lawrence Carin · 2015
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How (not) to train your generative model: Scheduled sampling, likelihood, adversary?
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Nips 2016 tutorial: Generative adversarial networks
Ian Goodfellow · 2016
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Plug & play generative networks: Conditional iterative generation of images in latent space
Anh Nguyen, Jason Yosinski, Yoshua Bengio, Alexey Dosovitskiy, and Jeff Clune · 2016
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Functional poisson approximation in kantorovich–rubinstein distance with applications to u-statistics and stochastic geometry
Laurent Decreusefond, Matthias Schulte, Christoph Thäle, et al · 2016
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Olof Mogren · 2016
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Contextual rnn-gans for abstract reasoning diagram generation
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Lucas Theis, Aäron van den Oord, and Matthias Bethge · 2015
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Recurrent marked temporal point processes: Embedding event history to vector
Nan Du, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, and Le Song · 2016
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Arnab Ghosh, Viveka Kulharia, Amitabha Mukerjee, Vinay Namboodiri, and Mohit Bansal · 2016
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Towards principled methods for training generative adversarial networks
Martin Arjovsky and Léon Bottou · 2017
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Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
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