%0 Conference Paper %1 ramchandran2021longitudinal %A Ramchandran, Siddharth %A Tikhonov, Gleb %A Kujanpää, Kalle %A Koskinen, Miika %A Lähdesmäki, Harri %B International Conference on Artificial Intelligence and Statistics %D 2021 %K imputation gain missing data generative model net nn deep learning autoencoder variational longitudinal temporal timeseries time series citedby:scholar:count:6 citedby:scholar:timestamp:2022-5-13 %P 3898--3906 %T Longitudinal variational autoencoder

@inproceedings{ramchandran2021longitudinal, added-at = {2022-05-14T01:13:25.000+0200}, author = {Ramchandran, Siddharth and Tikhonov, Gleb and Kujanp{\"a}{\"a}, Kalle and Koskinen, Miika and L{\"a}hdesm{\"a}ki, Harri}, biburl = {https://www.bibsonomy.org/bibtex/2bdfff5b60d95dd0c8a68a2529c359861/becker}, booktitle = {International Conference on Artificial Intelligence and Statistics}, interhash = {4d5bee04f3420bfb179a20096bd515ad}, intrahash = {bdfff5b60d95dd0c8a68a2529c359861}, keywords = {imputation gain missing data generative model net nn deep learning autoencoder variational longitudinal temporal timeseries time series citedby:scholar:count:6 citedby:scholar:timestamp:2022-5-13}, organization = {PMLR}, pages = {3898--3906}, timestamp = {2022-05-14T01:13:25.000+0200}, title = {Longitudinal variational autoencoder}, year = 2021 }