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cs.AI2018
Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations
Michael Harradon, Jeff Druce, Brian Ruttenberg
Deep neural networks are complex and opaque. As they enter application in a variety of important and safety critical domains, users seek methods to explain their output predictions…
cs.AI2016
Structured Factored Inference: A Framework for Automated Reasoning in Probabilistic Programming Languages
Avi Pfeffer, Brian Ruttenberg, William Kretschmer
Reasoning on large and complex real-world models is a computationally difficult task, yet one that is required for effective use of many AI applications. A plethora of inference al…