- Abstract:
-
In probabilistic inference, many implicit and explicit assumptions are taken about the nature of input noise and the function fit to either simplify the mathematics, improve the time complexity or optimise for space. It is often assumed that the inputs are noiseless or that the noise is drawn from the same distribution for all inputs, that all the variables used during training will be present during prediction and with the same degrees of uncertainties, and that the confidence about the p...
Expand abstract - Files:
-
-
(pdf, 23.8MB)
-
-
Version unsuitable
-
We have not obtained a suitable full-text for a given research output. See this page for more information.
-
Recently completed
-
Sometimes content is held in ORA but is unavailable for a fixed period of time to comply with the policies and wishes of rights holders.
-
Permissions
-
All content made available in ORA should comply with relevant rights, such as copyright. See this page for more information.
-
Clearance
-
Some thesis volumes scanned as part of the digitisation scheme funded by Dr Leonard Polonsky are currently unavailable due to sensitive material or uncleared third-party copyright content. We are attempting to contact authors whose theses are affected.
- Role:
- Supervisor
- Role:
- Supervisor
- Role:
- Examiner
- Role:
- Examiner
- Funding agency for:
- Ibrahim Almosallam
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
- Copyright date:
- 2017
Thesis
Heteroscedastic Gaussian processes for uncertain and incomplete data
Actions
Access Document
Why is the content I wish to access not available via ORA?
Bibliographic data (the information relating to research outputs) and full-text items (e.g. articles, theses, reports, etc.) arrive in ORA from several different sources. Unfortunately we are not able to make available the full-text for every research output.
Please contact the ORA team (
) if you have queries regarding unavailable content OR if you are aware of a full-text copy we can make available.
) if you have queries regarding unavailable content OR if you are aware of a full-text copy we can make available.
Content may be unavailable for the following four reasons
Alternative access to the full-text
You may be able to access the full-text directly from the publisher's website using the 'Publisher Copy' link in the 'Links & Downloads' box from a research output's ORA record page. This method may require an institutional or individual subscription to the journal/resource.
Authors
Contributors
+ Stephen Roberts
+ Matt Jarvis
+ Suzanne Aigrain
+ Richard Everson
Funding
+ King Abdulaziz City for Science and Technology
More from this funder
Bibliographic Details
Related Items
Terms of use
Metrics
Altmetrics
Dimensions
If you are the owner of this record, you can report an update to it here: Report update to this record