Modeling and generating human mobility trajectories using transformer with day encoding

Author:

Kobayashi Akihiro1ORCID,Takeda Naoto1ORCID,Yamazaki Yudai1ORCID,Kamisaka Daisuke1ORCID

Affiliation:

1. KDDI Research, Fujimino-shi, Japan

Funder

Ministry of Internal Affairs and Communications

Publisher

ACM

Reference7 articles.

1. Taizo Horikomi Shouji Fujimoto Atushi Ishikawa and Takayuki Mizuno. 2023. Generating Individual Trajectories Using GPT-2 Trained from Scratch on Encoded Spatiotemporal Data. arXiv:2308.07940 [cs.LG] Taizo Horikomi Shouji Fujimoto Atushi Ishikawa and Takayuki Mizuno. 2023. Generating Individual Trajectories Using GPT-2 Trained from Scratch on Encoded Spatiotemporal Data. arXiv:2308.07940 [cs.LG]

2. Generation of individual daily trajectories by GPT-2

3. Alec Radford Jeffrey Wu Rewon Child David Luan Dario Amodei and Ilya Sutskever. 2018. Language Models are Unsupervised Multitask Learners. (2018). https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf Alec Radford Jeffrey Wu Rewon Child David Luan Dario Amodei and Ilya Sutskever. 2018. Language Models are Unsupervised Multitask Learners. (2018). https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf

4. Neural Machine Translation of Rare Words with Subword Units

5. GEO-BLEU

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