CoLES: Contrastive Learning for Event Sequences with Self-Supervision

Summary: CoLES adapts contrastive self-supervision to discrete event sequences, producing fixed-length embeddings for downstream tasks. Real-world deployment at a large European financial services company yields hundreds of millions in annual gains, with public datasets showing consistent improvements over baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6443
Venue: SIGMOD
Year: 2022
Pagerank: 4.3254416e-05
Overall Rank: 9,562 | 33.48%
DOI: 10.1145/3514221.3526129

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,035	SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine	2026	SIGMOD	4.1945683e-05

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