Learning from Nested Data with Ornstein Auto-Encoders

                   Youngwon Choi 1 2 Sungdong Lee 1 Joong-Ho Won 1

              Abstract                  ture for each digit. In multicenter electronic health records,
                                    patients are nested within a hospital. For such nested data,
   Many of real-world data, e.g., the VGGFace2            representation learning aims to find a representation where
   dataset, which is a collection of multiple por-          ...