[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-autoencoder":3},{"tag":4,"articles":9},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":8},"ca376ab9-2d23-4de3-b4be-182ab8ac03eb","autoencoder",1,null,[10],{"id":11,"slug":12,"title":13,"summary":14,"category":15,"image_url":16,"cover_image":16,"language":17,"created_at":18},"94a303d1-8715-447d-8eaa-16f39c66162d","geometric-regularization-autoencoders-stochastic-dynamics-zh","自編碼器學隨機動態也要顧幾何","這篇論文把切空間與逆一致性正則化加進自編碼器，用來從高維隨機資料學更可靠的降維模擬器。","research","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1776665225839-hu3t.png","zh","2026-04-20T06:06:35.154782+00:00"]