Diagnostic Visualization for Deep Neural Networks Using Stochastic Gradient Langevin Dynamics

11 Dec 2018Biye JiangDavid M. ChanTianhao ZhangJohn F. Canny

The internal states of most deep neural networks are difficult to interpret, which makes diagnosis and debugging during training challenging. Activation maximization methods are widely used, but lead to multiple optima and are hard to interpret (appear noise-like) for complex neurons... (read more)

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