- Abstract:
-
We introduce a probabilistic model for the factorisation of continuous Poisson process rate functions. Our model can be thought of as a topic model for Poisson point processes in which each point is assigned to one of a set of latent rate functions that are shared across multiple outputs. We show that the model brings a means of incorporating structure in point process inference beyond the state-of-the-art. We derive an efficient variational inference scheme for the model based on sparse Gaus...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's version
- Funding agency for:
- Nickson, T
- Publisher:
- Journal of Machine Learning Research Publisher's website
- Volume:
- 41
- Pages:
- 389-397
- Publication date:
- 2016
- Acceptance date:
- 2015-10-09
- ISSN:
-
1938-7228
- Pubs id:
-
pubs:664826
- URN:
-
uri:bd7bb398-fbe7-41ee-92d3-79341f46afec
- UUID:
-
uuid:bd7bb398-fbe7-41ee-92d3-79341f46afec
- Local pid:
- pubs:664826
- Copyright holder:
- Lloyd et al.
- Copyright date:
- 2016
- Notes:
-
Copyright
2016 by the authors.
Conference item
Latent point process allocation
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+ Engineering and Physical Sciences Research Council
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