{"action":"created","issue":{"url":"https://api.github.com/repos/mtewes/tenbilac/issues/14","repository_url":"https://api.github.com/repos/mtewes/tenbilac","labels_url":"https://api.github.com/repos/mtewes/tenbilac/issues/14/labels{/name}","comments_url":"https://api.github.com/repos/mtewes/tenbilac/issues/14/comments","events_url":"https://api.github.com/repos/mtewes/tenbilac/issues/14/events","html_url":"https://github.com/mtewes/tenbilac/issues/14","id":191536184,"number":14,"title":"Adding \"Product Unit\" neurons (or layers)","user":{"login":"mtewes","id":1928653,"avatar_url":"https://avatars.githubusercontent.com/u/1928653?v=3","gravatar_id":"","url":"https://api.github.com/users/mtewes","html_url":"https://github.com/mtewes","followers_url":"https://api.github.com/users/mtewes/followers","following_url":"https://api.github.com/users/mtewes/following{/other_user}","gists_url":"https://api.github.com/users/mtewes/gists{/gist_id}","starred_url":"https://api.github.com/users/mtewes/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mtewes/subscriptions","organizations_url":"https://api.github.com/users/mtewes/orgs","repos_url":"https://api.github.com/users/mtewes/repos","events_url":"https://api.github.com/users/mtewes/events{/privacy}","received_events_url":"https://api.github.com/users/mtewes/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":5,"created_at":"2016-11-24T14:42:02Z","updated_at":"2016-11-25T15:49:56Z","closed_at":null,"body":"There is quite a bit of litterature on multiplicative networks, and it sounds very good so far, nice!\r\nOne paper I like a lot is:\r\nhttp://sci2s.ugr.es/keel/pdf/specific/articulo/Schmidtt%20on-the-complexity-of.pdf\r\n\r\nWill work on this in a dedicated branch #14\r\n"},"comment":{"url":"https://api.github.com/repos/mtewes/tenbilac/issues/comments/262984032","html_url":"https://github.com/mtewes/tenbilac/issues/14#issuecomment-262984032","issue_url":"https://api.github.com/repos/mtewes/tenbilac/issues/14","id":262984032,"user":{"login":"mtewes","id":1928653,"avatar_url":"https://avatars.githubusercontent.com/u/1928653?v=3","gravatar_id":"","url":"https://api.github.com/users/mtewes","html_url":"https://github.com/mtewes","followers_url":"https://api.github.com/users/mtewes/followers","following_url":"https://api.github.com/users/mtewes/following{/other_user}","gists_url":"https://api.github.com/users/mtewes/gists{/gist_id}","starred_url":"https://api.github.com/users/mtewes/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mtewes/subscriptions","organizations_url":"https://api.github.com/users/mtewes/orgs","repos_url":"https://api.github.com/users/mtewes/repos","events_url":"https://api.github.com/users/mtewes/events{/privacy}","received_events_url":"https://api.github.com/users/mtewes/received_events","type":"User","site_admin":false},"created_at":"2016-11-25T15:49:56Z","updated_at":"2016-11-25T15:49:56Z","body":"I pushed the demo code, \r\ndemo/test_mult_learn.py\r\n\r\nOne big issue to think about is the \"normalization\", the issues with negative values fed into \"product units\", and the choice of activation functions that get \"fed\" into later product-unit layers. It's a whole new world to explore, but I would love to not explore it for too long :)\r\nI guess it would be good to keep the \"signs\" of ellipticity components somehow, i.e. use a \"-11\" norm, and find a hack so that it works with the product units. Using a \"01\" normer in front of a product unit would be a shame. We precisely want those units to be able to rescale numbers which might be positive or negative by multiplying their amplitude. Maybe some power-raising that artificially keeps the sign could work (and reinventing maths is fun)."}}
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