mlsanityData to 7 Oct 2026

RNADE: The real-valued neural autoregressive density-estimator

arXiv 1306.0186 ↗First posted 2 Jun 2013stat.ML cs.LGcited by 65

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Abstract (arXiv)

We introduce RNADE, a new model for joint density estimation of real-valued vectors. Our model calculates the density of a datapoint as the product of one-dimensional conditionals modeled using mixture density networks with shared parameters. RNADE learns a distributed representation of the data, while having a tractable expression for the calculation of densities. A tractable likelihood allows direct comparison with other methods and training by standard gradient-based optimizers. We compare the performance of RNADE on several datasets of heterogeneous and perceptual data, finding it outperforms mixture models in all but one case.

Key facts. Cited by 65 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jun 2013.

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Citing papers per year: 2021: 20; 2022: 16; 2023: 15; 2024: 10; 2025: 4.

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