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OR-Net: Pointwise Relational Inference for Data Completion under Partial Observation
[article]
2021
arXiv
pre-print
Contemporary data-driven methods are typically fed with full supervision on large-scale datasets which limits their applicability. However, in the actual systems with limitations such as measurement error and data acquisition problems, people usually obtain incomplete data. Although data completion has attracted wide attention, the underlying data pattern and relativity are still under-developed. Currently, the family of latent variable models allows learning deep latent variables over observed
arXiv:2105.00397v2
fatcat:bpq6beyy7fgtdkiclvg3tighde