Recently, neural models such as cascaded residual autoencoders (Tran et al., 2017), deep adversarial learning (Cai et al., 2018), or translation-based learning (Pham et al., 2019) have also been proposed.
these methods often require knowing which of the entries or modalities are imperfect beforehand.