{"action":"opened","issue":{"url":"https://api.github.com/repos/wyndwarrior/Sectar/issues/2","repository_url":"https://api.github.com/repos/wyndwarrior/Sectar","labels_url":"https://api.github.com/repos/wyndwarrior/Sectar/issues/2/labels{/name}","comments_url":"https://api.github.com/repos/wyndwarrior/Sectar/issues/2/comments","events_url":"https://api.github.com/repos/wyndwarrior/Sectar/issues/2/events","html_url":"https://github.com/wyndwarrior/Sectar/issues/2","id":485651479,"node_id":"MDU6SXNzdWU0ODU2NTE0Nzk=","number":2,"title":"Effect of min_log_var usage","user":{"login":"ZhuFengdaaa","id":9649227,"node_id":"MDQ6VXNlcjk2NDkyMjc=","avatar_url":"https://avatars0.githubusercontent.com/u/9649227?v=4","gravatar_id":"","url":"https://api.github.com/users/ZhuFengdaaa","html_url":"https://github.com/ZhuFengdaaa","followers_url":"https://api.github.com/users/ZhuFengdaaa/followers","following_url":"https://api.github.com/users/ZhuFengdaaa/following{/other_user}","gists_url":"https://api.github.com/users/ZhuFengdaaa/gists{/gist_id}","starred_url":"https://api.github.com/users/ZhuFengdaaa/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ZhuFengdaaa/subscriptions","organizations_url":"https://api.github.com/users/ZhuFengdaaa/orgs","repos_url":"https://api.github.com/users/ZhuFengdaaa/repos","events_url":"https://api.github.com/users/ZhuFengdaaa/events{/privacy}","received_events_url":"https://api.github.com/users/ZhuFengdaaa/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2019-08-27T08:04:28Z","updated_at":"2019-08-27T08:04:28Z","closed_at":null,"author_association":"NONE","body":"I notice that in `gaussian_network.py`, you use `min_log_var` in `GaussianNetwork` class to ensure the variance of z distribution not too low. However, not all subclass use this variable(e.g. GaussianBidirectionalNetwork). I am wondering why we need this variable and how this variable effect training? \r\n\r\nThank you :)"}}
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