Meta-Learning MCMC Proposals

NeurIPS 2018 Tongzhou WangYi WuDavid A. MooreStuart J. Russell

Effective implementations of sampling-based probabilistic inference often require manually constructed, model-specific proposals. Inspired by recent progresses in meta-learning for training learning agents that can generalize to unseen environments, we propose a meta-learning approach to building effective and generalizable MCMC proposals... (read more)

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