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Limitations of Autoregressive Models in Probabilistic Modeling

The current focus on autoregressive models in machine learning may not effectively capture the underlying distribution of complex, structured data. Joint probability modeling is mathematically more suitable but faces computational challenges. The field may have prematurely adopted easier-to-compute conditional probabilities.

Computing & Technology, Computer Science, Machine Learning