Conference item
Gaussian processes for survival analysis
- Abstract:
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We introduce a semi-parametric Bayesian model for survival analysis. The model is centred on a parametric baseline hazard, and uses a Gaussian process to model variations away from it nonparametrically, as well as dependence on covariates. As opposed to many other methods in survival analysis, our framework does not impose unnecessary constraints in the hazard rate or in the survival function. Furthermore, our model handles left, right and interval censoring mechanisms common in survival anal...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Accepted manuscript, pdf, 1.1MB)
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Authors
Funding
Bibliographic Details
- Publisher:
- Curran Associates Publisher's website
- Volume:
- 29
- Pages:
- 5021-5029
- Host title:
- Advances in Neural Information Processing Systems 29: 30th Annual Conference on Neural Information Processing Systems 2016
- Publication date:
- 2016-12-05
- Acceptance date:
- 2016-09-04
- Event location:
- Barcelona, Spain
- Event start date:
- 2016-12-05T00:00:00Z
- Event end date:
- 2016-12-08T00:00:00Z
- ISSN:
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1049-5258
- Source identifiers:
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661533
- ISBN:
- 9781510838819
Item Description
- Pubs id:
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pubs:661533
- UUID:
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uuid:db03c8ae-6e6b-4fdd-8c3d-edd217113b47
- Local pid:
- pubs:661533
- Deposit date:
- 2016-11-24
Terms of use
- Copyright holder:
- Neural Information Processing Systems Foundation, Inc
- Copyright date:
- 2016
- Notes:
- Proceedings of a meeting held 5-10 December 2016, Barcelona, Spain.
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