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08/31/2023
Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing
Uncovering novel drug candidates for treating complex diseases remain on...
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11/25/2021
Learning Conditional Invariance through Cycle Consistency
Identifying meaningful and independent factors of variation in a dataset...
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02/07/2020
Inverse Learning of Symmetry Transformations
Symmetry transformations induce invariances and are a crucial building b...
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02/03/2020
Learning Extremal Representations with Deep Archetypal Analysis
Archetypes are typical population representatives in an extremal sense, ...
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01/30/2019
Deep Archetypal Analysis
"Deep Archetypal Analysis" generates latent representations of high-dime...
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11/26/2018
Estimating Causal Effects With Partial Covariates For Clinical Interpretability
Estimating the causal effects of an intervention in the presence of conf...
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11/19/2018
Informed MCMC with Bayesian Neural Networks for Facial Image Analysis
Computer vision tasks are difficult because of the large variability in ...
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07/06/2018
Causal Deep Information Bottleneck
Estimating causal effects in the presence of latent confounding is a fre...
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04/17/2018
