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06/11/2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates
Both uncertainty estimation and interpretability are important factors f...
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11/21/2019
Continual Learning with Adaptive Weights (CLAW)
Approaches to continual learning aim to successfully learn a set of rela...
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10/16/2019
Conditional Learning of Fair Representations
We propose a novel algorithm for learning fair representations that can ...
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02/15/2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis
This article presents the prediction difference analysis method for visu...
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08/27/2016
Learning Bayesian Networks with Incomplete Data by Augmentation
We present new algorithms for learning Bayesian networks from data with ...
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06/28/2016
Automatic Variational ABC
Approximate Bayesian Computation (ABC) is a framework for performing lik...
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08/03/2015
A Weakly Supervised Learning Approach based on Spectral Graph-Theoretic Grouping
In this study, a spectral graph-theoretic grouping strategy for weakly s...
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09/26/2013