Deep Directed Generative Models with Energy-Based Probability Estimation

10 Jun 2016Taesup KimYoshua Bengio

Training energy-based probabilistic models is confronted with apparently intractable sums, whose Monte Carlo estimation requires sampling from the estimated probability distribution in the inner loop of training. This can be approximately achieved by Markov chain Monte Carlo methods, but may still face a formidable obstacle that is the difficulty of mixing between modes with sharp concentrations of probability... (read more)

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