First dedicated survey organizing diffusion and flow matching models for tabular data synthesis, imputation, anomaly detection, and related tasks, covering literature from 2015 to 2026 and highlighting open problems.
Multilayer feedforward networks are universal approximators
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Model-based stochastic dual gradient and model-free primal-dual deep learning algorithms are proposed and simulated for optimal WDM power allocation in RoFSO systems, outperforming equal power allocation.
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Diffusion and Flow Matching Models for Tabular Data: A Survey
First dedicated survey organizing diffusion and flow matching models for tabular data synthesis, imputation, anomaly detection, and related tasks, covering literature from 2015 to 2026 and highlighting open problems.
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Optimal WDM Power Allocation via Deep Learning for Radio on Free Space Optics Systems
Model-based stochastic dual gradient and model-free primal-dual deep learning algorithms are proposed and simulated for optimal WDM power allocation in RoFSO systems, outperforming equal power allocation.