oates.work valuation and analysis
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Meta Tags
| Title | Chris |
| Description | Chris Oates Professional Papers Presentations Teaching Carbon Contact Menu Street Address City, State, Zip Phone Number Your Custom Text Here Chris Oates |
| Keywords | N/A |
Server Information
| WebSite | |
| Host IP | 198.49.23.145 |
| Location | United States |
Related Websites
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oates.work Valuation
|
US$1,599,812
Last updated: 2023-05-18 17:58:42
oates.work has Semrush global rank of 6,615,967. oates.work has an estimated worth of US$ 1,599,812, based on its estimated Ads revenue. oates.work receives approximately 184,594 unique visitors each day. Its web server is located in United States, with IP address 198.49.23.145. According to SiteAdvisor, oates.work is safe to visit. |
Traffic & Worth Estimates
| Purchase/Sale Value | US$1,599,812 |
| Daily Ads Revenue | US$1,477 |
| Monthly Ads Revenue | US$44,303 |
| Yearly Ads Revenue | US$531,630 |
| Daily Unique Visitors | 12,307 |
| Note: All traffic and earnings values are estimates. | |
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| oates.work. | A | 14399 | IP: 198.49.23.144 |
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HtmlToTextCheckTime:2023-05-18 17:58:42
| Chris Oates Professional Papers Presentations Teaching Carbon Contact Menu Street Address City, State, Zip Phone Number Your Custom Text Here Chris Oates Professional Papers Presentations Teaching Carbon Contact I am currently a Professor of Statistics at Newcastle University and a Turing Fellow / Group Leader on the Programme for Data-Centric Engineering at the Alan Turing Institute, UK. I am interested in computational statistics, kernel methods, machine learning, and uncertainty quantification. Recent News Our paper “Meta-learning Control Variates: Variance Reduction with Limited Data” was selected for an oral presentation at UAI 2023 . I have been awarded £0.8M to research methodologies based on Stein Discrepancies for Bayesian computation , funded by EPSRC (2022-2026). I am Co-Investigator on a new £1.1M CDT, called NUData , funded by STFC (2022-2028). Two new papers accepted in JRSSB : Optimal Thinning of MCMC Output and Robust Generalised Bayesian Inference for Intractable |
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