[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-latent-sde":3},{"tag":4,"articles":10},{"id":5,"name":6,"slug":7,"article_count":8,"description_zh":9,"description_en":9},"71650ee5-12b5-4d98-97f4-dbe75b1862dc","latent SDE","latent-sde",2,null,[11],{"id":12,"slug":13,"title":14,"summary":15,"category":16,"image_url":17,"cover_image":17,"language":18,"created_at":19},"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"]