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- Argonne National LaboratoryUS306 papers
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96 papers · 1 filter
On Connecting Stochastic Gradient MCMC and Differential Privacy
Bai Li, Changyou Chen, Hao Liu +1
Significant success has been realized recently on applying machine learning to real-world applications. There have also been corresponding concerns on the privacy of training data,…
Low Background Materials and Fabrication Techniques for Cables and Connectors in the Majorana Demonstrator
M. Busch, N. Abgrall, S. I. Alvis +67
The MAJORANA Collaboration is searching for the neutrinoless double-beta decay of the nucleus Ge-76. The MAJORANA DEMONSTRATOR is an array of germanium detectors deployed with the…
Multiplicative Coevolution Regression Models for Longitudinal Networks and Nodal Attributes
Yanjun He, Peter D. Hoff
We introduce a simple and extendable coevolution model for the analysis of longitudinal network and nodal attribute data. The model features parameters that describe three phenomen…
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ
Zhe Zhu, Michael Harowicz, Jun Zhang +4
Purpose: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the di- agnosis of ductal ca…
Contamination Control and Assay Results for the Majorana Demonstrator Ultra Clean Components
C. D. Christofferson, N. Abgrall, S. I. Alvis +67
The MAJORANA DEMONSTRATOR is a neutrinoless double beta decay experiment utilizing enriched Ge-76 detectors in 2 separate modules inside of a common solid shield at the Sanford Und…
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions
Oscar Li, Hao Liu, Chaofan Chen +1
Deep neural networks are widely used for classification. These deep models often suffer from a lack of interpretability -- they are particularly difficult to understand because of…