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MFPP: Morphological Fragmental Perturbation Pyramid for Black-Box Model Explanations
With the increasing popularity of deep neural networks (DNNs), it has re...
06/04/2020 ∙ by Qing Yang, et al. ∙
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Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis
With the wide adoption of functional magnetic resonance imaging (fMRI) b...
05/11/2020 ∙ by Ming Bo Cai, et al. ∙
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PipeNet: Selective Modal Pipeline of Fusion Network for Multi-Modal Face Anti-Spoofing
Face anti-spoofing has become an increasingly important and critical sec...
04/24/2020 ∙ by Qing Yang, et al. ∙
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Channel Pruning via Optimal Thresholding
Structured pruning, especially channel pruning is widely used for the re...
03/10/2020 ∙ by Yun Ye, et al. ∙
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Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers
As deep learning methods form a critical part in commercially important ...
09/04/2018 ∙ by Apoorv Vyas, et al. ∙
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Segmenting Brain Tumors with Symmetry
We explore encoding brain symmetry into a neural network for a brain tum...
11/17/2017 ∙ by Hejia Zhang, et al. ∙
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A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis
There is a growing interest in joint multi-subject fMRI analysis. The ch...
09/29/2016 ∙ by Hejia Zhang, et al. ∙
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A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation
Finding the most effective way to aggregate multi-subject fMRI data is a...
08/17/2016 ∙ by Po-Hsuan Chen, et al. ∙
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Enabling Factor Analysis on Thousand-Subject Neuroimaging Datasets
The scale of functional magnetic resonance image data is rapidly increas...
08/16/2016 ∙ by Michael J. Anderson, et al. ∙
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