{"action":"created","issue":{"url":"https://api.github.com/repos/uber/pyro/issues/1630","repository_url":"https://api.github.com/repos/uber/pyro","labels_url":"https://api.github.com/repos/uber/pyro/issues/1630/labels{/name}","comments_url":"https://api.github.com/repos/uber/pyro/issues/1630/comments","events_url":"https://api.github.com/repos/uber/pyro/issues/1630/events","html_url":"https://github.com/uber/pyro/pull/1630","id":387707528,"node_id":"MDExOlB1bGxSZXF1ZXN0MjM2MTM0NTYx","number":1630,"title":"Bayesian Regression Part II","user":{"login":"jpchen","id":1869641,"node_id":"MDQ6VXNlcjE4Njk2NDE=","avatar_url":"https://avatars2.githubusercontent.com/u/1869641?v=4","gravatar_id":"","url":"https://api.github.com/users/jpchen","html_url":"https://github.com/jpchen","followers_url":"https://api.github.com/users/jpchen/followers","following_url":"https://api.github.com/users/jpchen/following{/other_user}","gists_url":"https://api.github.com/users/jpchen/gists{/gist_id}","starred_url":"https://api.github.com/users/jpchen/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jpchen/subscriptions","organizations_url":"https://api.github.com/users/jpchen/orgs","repos_url":"https://api.github.com/users/jpchen/repos","events_url":"https://api.github.com/users/jpchen/events{/privacy}","received_events_url":"https://api.github.com/users/jpchen/received_events","type":"User","site_admin":false},"labels":[{"id":704807577,"node_id":"MDU6TGFiZWw3MDQ4MDc1Nzc=","url":"https://api.github.com/repos/uber/pyro/labels/WIP","name":"WIP","color":"fbca04","default":false}],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":3,"created_at":"2018-12-05T11:12:07Z","updated_at":"2018-12-07T01:57:17Z","closed_at":null,"author_association":"MEMBER","pull_request":{"url":"https://api.github.com/repos/uber/pyro/pulls/1630","html_url":"https://github.com/uber/pyro/pull/1630","diff_url":"https://github.com/uber/pyro/pull/1630.diff","patch_url":"https://github.com/uber/pyro/pull/1630.patch"},"body":"part ii\r\n\r\n**TODO**\r\n- [ ] mvn transforms in guide\r\n- [ ] more descriptions on dist choices\r\n- [ ] references for algorithms"},"comment":{"url":"https://api.github.com/repos/uber/pyro/issues/comments/445095991","html_url":"https://github.com/uber/pyro/pull/1630#issuecomment-445095991","issue_url":"https://api.github.com/repos/uber/pyro/issues/1630","id":445095991,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0NTA5NTk5MQ==","user":{"login":"neerajprad","id":1762463,"node_id":"MDQ6VXNlcjE3NjI0NjM=","avatar_url":"https://avatars3.githubusercontent.com/u/1762463?v=4","gravatar_id":"","url":"https://api.github.com/users/neerajprad","html_url":"https://github.com/neerajprad","followers_url":"https://api.github.com/users/neerajprad/followers","following_url":"https://api.github.com/users/neerajprad/following{/other_user}","gists_url":"https://api.github.com/users/neerajprad/gists{/gist_id}","starred_url":"https://api.github.com/users/neerajprad/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/neerajprad/subscriptions","organizations_url":"https://api.github.com/users/neerajprad/orgs","repos_url":"https://api.github.com/users/neerajprad/repos","events_url":"https://api.github.com/users/neerajprad/events{/privacy}","received_events_url":"https://api.github.com/users/neerajprad/received_events","type":"User","site_admin":false},"created_at":"2018-12-07T01:57:17Z","updated_at":"2018-12-07T01:57:17Z","author_association":"COLLABORATOR","body":"> you mean diagnormal guide? the autoguide was in the first part. i can do the mvn one we have the plots for comparisons already, i just need to use a better variational initialization i will update it and you can see if it's necessary\r\n\r\nSorry, I completely missed that we ended up using the autoguide in the first part itself. My impression was that we were going to not invoke auto-guides in that. I think the diagnormal guide works great as a comparison against HMC, as it is instructive to see the implications of the modeling assumptions i.e. independent latents, and the under-dispersion due to Klqp loss. Are we planning to do that first before comparing again the mvn guide? "}}
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