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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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We consider how a prediction service can implement an “insurance” against misprediction, such that its customers can use each prediction as if it is perfectly correct. The insurance can be implemented at provably no cost to the prediction service (in the long run).
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We propose a framework to systematically investigate bias and generalization in deep generative models of images. Inspired by experimental methods from cognitive psychology, we probe each learning algorithm with carefully designed training datasets to characterize when and how existing models generate novel attributes and their combinations.
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This tutorial discusses MMD variational autoencoders, a member of the InfoVAE family. It is an alternative to traditional variational autoencoders that is fast to train, stable, and easy to implement.
Short description of portfolio item number 1
Short description of portfolio item number 2
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.