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Neural Process
A meta-learning model that learns a distribution over functions conditioned on context points (observed input-output pairs), enabling fast adaptation to new tasks. Neural Processes combine the representational power of neural networks with the flexibility of Gaussian Processes. In robotics, NPs enable few-shot adaptation of manipulation policies from a few new demonstrations.