Using synthetic data to train neural networks is model-based reasoning
We draw a formal connection between using synthetic training data to optimize neural
network parameters and approximate, Bayesian, model-based reasoning. In particular,
training a neural network using synthetic data can be viewed as learning a proposal
distribution generator for approximate inference in the synthetic-data generative model. We
demonstrate this connection in a recognition task where we develop a novel Captcha-
breaking architecture and train it using synthetic data, demonstrating both state-of-the-art …
network parameters and approximate, Bayesian, model-based reasoning. In particular,
training a neural network using synthetic data can be viewed as learning a proposal
distribution generator for approximate inference in the synthetic-data generative model. We
demonstrate this connection in a recognition task where we develop a novel Captcha-
breaking architecture and train it using synthetic data, demonstrating both state-of-the-art …
Using Synthetic Data to Train Neural Networks is Model− Based Reasoning
AG Baydin - 2017 - cs.ox.ac.uk
We draw a formal connection between using synthetic training data to optimize neural
network parameters and approximate, Bayesian, model-based reasoning. In particular,
training a neural network using synthetic data can be viewed as learning a proposal
distribution generator for approximate inference in the synthetic-data generative model. We
demonstrate this connection in a recognition task where we develop a novel Captcha-
breaking architecture and train it using synthetic data, demonstrating both state-of-the-art …
network parameters and approximate, Bayesian, model-based reasoning. In particular,
training a neural network using synthetic data can be viewed as learning a proposal
distribution generator for approximate inference in the synthetic-data generative model. We
demonstrate this connection in a recognition task where we develop a novel Captcha-
breaking architecture and train it using synthetic data, demonstrating both state-of-the-art …
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