{"action":"created","issue":{"url":"https://api.github.com/repos/pymc-devs/pymc3/issues/2951","repository_url":"https://api.github.com/repos/pymc-devs/pymc3","labels_url":"https://api.github.com/repos/pymc-devs/pymc3/issues/2951/labels{/name}","comments_url":"https://api.github.com/repos/pymc-devs/pymc3/issues/2951/comments","events_url":"https://api.github.com/repos/pymc-devs/pymc3/issues/2951/events","html_url":"https://github.com/pymc-devs/pymc3/pull/2951","id":317691709,"node_id":"MDExOlB1bGxSZXF1ZXN0MTg0MDg0Njcz","number":2951,"title":"SparseLatent GP","user":{"login":"smartass101","id":941907,"node_id":"MDQ6VXNlcjk0MTkwNw==","avatar_url":"https://avatars0.githubusercontent.com/u/941907?v=4","gravatar_id":"","url":"https://api.github.com/users/smartass101","html_url":"https://github.com/smartass101","followers_url":"https://api.github.com/users/smartass101/followers","following_url":"https://api.github.com/users/smartass101/following{/other_user}","gists_url":"https://api.github.com/users/smartass101/gists{/gist_id}","starred_url":"https://api.github.com/users/smartass101/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/smartass101/subscriptions","organizations_url":"https://api.github.com/users/smartass101/orgs","repos_url":"https://api.github.com/users/smartass101/repos","events_url":"https://api.github.com/users/smartass101/events{/privacy}","received_events_url":"https://api.github.com/users/smartass101/received_events","type":"User","site_admin":false},"labels":[{"id":483431340,"node_id":"MDU6TGFiZWw0ODM0MzEzNDA=","url":"https://api.github.com/repos/pymc-devs/pymc3/labels/WIP","name":"WIP","color":"d93f0b","default":false}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":34,"created_at":"2018-04-25T15:58:08Z","updated_at":"2018-08-19T08:32:02Z","closed_at":null,"author_association":"CONTRIBUTOR","pull_request":{"url":"https://api.github.com/repos/pymc-devs/pymc3/pulls/2951","html_url":"https://github.com/pymc-devs/pymc3/pull/2951","diff_url":"https://github.com/pymc-devs/pymc3/pull/2951.diff","patch_url":"https://github.com/pymc-devs/pymc3/pull/2951.patch"},"body":"This is an attempt based on [this notebook](https://gist.github.com/bwengals/a0357d75d2083657a2eac85947381a44) by @bwengals to implement the DTC and FITC sparse approximations.\r\n\r\nI tried to read through [Quinonero-Candela+Rasmussen, 2006](http://www.jmlr.org/papers/v6/quinonero-candela05a.html) for the covariance equations. Essentially I substituted `sigma=0` in them and reduced them to simpler and yet computationally feasible forms. But it's quite likely my code is un-optimal and wrong."},"comment":{"url":"https://api.github.com/repos/pymc-devs/pymc3/issues/comments/414112520","html_url":"https://github.com/pymc-devs/pymc3/pull/2951#issuecomment-414112520","issue_url":"https://api.github.com/repos/pymc-devs/pymc3/issues/2951","id":414112520,"node_id":"MDEyOklzc3VlQ29tbWVudDQxNDExMjUyMA==","user":{"login":"smartass101","id":941907,"node_id":"MDQ6VXNlcjk0MTkwNw==","avatar_url":"https://avatars0.githubusercontent.com/u/941907?v=4","gravatar_id":"","url":"https://api.github.com/users/smartass101","html_url":"https://github.com/smartass101","followers_url":"https://api.github.com/users/smartass101/followers","following_url":"https://api.github.com/users/smartass101/following{/other_user}","gists_url":"https://api.github.com/users/smartass101/gists{/gist_id}","starred_url":"https://api.github.com/users/smartass101/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/smartass101/subscriptions","organizations_url":"https://api.github.com/users/smartass101/orgs","repos_url":"https://api.github.com/users/smartass101/repos","events_url":"https://api.github.com/users/smartass101/events{/privacy}","received_events_url":"https://api.github.com/users/smartass101/received_events","type":"User","site_admin":false},"created_at":"2018-08-19T08:32:02Z","updated_at":"2018-08-19T08:32:02Z","author_association":"CONTRIBUTOR","body":"Well, I was mostly waiting for you @bwengals to reach a conclusion since you wrote this above.\r\n\r\n>  I'd want to spend a bit of time thinking about it, and maybe write it and play with it a bit before coming to a conclusion.\r\n\r\nPersonally, I'm still for implementing `.conditional_approx`."}}
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