{"action":"created","issue":{"url":"https://api.github.com/repos/pytorch/pytorch/issues/5988","repository_url":"https://api.github.com/repos/pytorch/pytorch","labels_url":"https://api.github.com/repos/pytorch/pytorch/issues/5988/labels{/name}","comments_url":"https://api.github.com/repos/pytorch/pytorch/issues/5988/comments","events_url":"https://api.github.com/repos/pytorch/pytorch/issues/5988/events","html_url":"https://github.com/pytorch/pytorch/pull/5988","id":308320709,"number":5988,"title":"[distributions] Implement MultivariateNormal.mean, .variance","user":{"login":"fritzo","id":648532,"avatar_url":"https://avatars0.githubusercontent.com/u/648532?v=4","gravatar_id":"","url":"https://api.github.com/users/fritzo","html_url":"https://github.com/fritzo","followers_url":"https://api.github.com/users/fritzo/followers","following_url":"https://api.github.com/users/fritzo/following{/other_user}","gists_url":"https://api.github.com/users/fritzo/gists{/gist_id}","starred_url":"https://api.github.com/users/fritzo/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fritzo/subscriptions","organizations_url":"https://api.github.com/users/fritzo/orgs","repos_url":"https://api.github.com/users/fritzo/repos","events_url":"https://api.github.com/users/fritzo/events{/privacy}","received_events_url":"https://api.github.com/users/fritzo/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-03-25T04:11:38Z","updated_at":"2018-03-25T07:25:05Z","closed_at":null,"author_association":"CONTRIBUTOR","pull_request":{"url":"https://api.github.com/repos/pytorch/pytorch/pulls/5988","html_url":"https://github.com/pytorch/pytorch/pull/5988","diff_url":"https://github.com/pytorch/pytorch/pull/5988.diff","patch_url":"https://github.com/pytorch/pytorch/pull/5988.patch"},"body":"Previous review: https://github.com/probtorch/pytorch/pull/141\r\n\r\n## Tested\r\n\r\n- added tests against scipy.stats"},"comment":{"url":"https://api.github.com/repos/pytorch/pytorch/issues/comments/375950958","html_url":"https://github.com/pytorch/pytorch/pull/5988#issuecomment-375950958","issue_url":"https://api.github.com/repos/pytorch/pytorch/issues/5988","id":375950958,"user":{"login":"fritzo","id":648532,"avatar_url":"https://avatars0.githubusercontent.com/u/648532?v=4","gravatar_id":"","url":"https://api.github.com/users/fritzo","html_url":"https://github.com/fritzo","followers_url":"https://api.github.com/users/fritzo/followers","following_url":"https://api.github.com/users/fritzo/following{/other_user}","gists_url":"https://api.github.com/users/fritzo/gists{/gist_id}","starred_url":"https://api.github.com/users/fritzo/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fritzo/subscriptions","organizations_url":"https://api.github.com/users/fritzo/orgs","repos_url":"https://api.github.com/users/fritzo/repos","events_url":"https://api.github.com/users/fritzo/events{/privacy}","received_events_url":"https://api.github.com/users/fritzo/received_events","type":"User","site_admin":false},"created_at":"2018-03-25T07:25:05Z","updated_at":"2018-03-25T07:25:05Z","author_association":"CONTRIBUTOR","body":"@SsnL you can get the precision matrix via `torch.inverse(mvn.covariance_matrix)` for a `MultivariateNormal` instance `mvn`. This PR doesn't really add any new algorithms; rather it provides two properties that are standardized across distributions. "}}
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