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Found 6 papers, 0 papers with code
Efficient semi-supervised inference for logistic regression under case-control studies
We find out that with the availability of the unlabeled data, the intercept parameter can be identified in semi-supervised learning setting.
Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN
In this work, a novel Multidirectional Perception Generative Adversarial Network (MP-GAN) is proposed to visualize the morphological features indicating the severity of AD for patients of different stages.
Magnetic properties of transition metal dimers probed by inelastic neutron scattering
Amongst the many characterisation techniques employed in such a task, Inelastic Neutron Scattering (INS) stands as one of the most powerful and sensitive tools to investigate their spin dynamics.
Mesoscale and Nanoscale Physics
Brain Stroke Lesion Segmentation Using Consistent Perception Generative Adversarial Network
The assistant network and the discriminator are employed to jointly decide whether the segmentation results are real or fake.
Tensorizing GAN with High-Order Pooling for Alzheimer's Disease Assessment
To the best of our knowledge, the proposed Tensor-train, High-pooling and Semi-supervised learning based GAN (THS-GAN) is the first work to deal with classification on MRI images for AD diagnosis.
Conditional probability calculation using restricted Boltzmann machine with application to system identification
There are many advantages to use probability method for nonlinear system identification, such as the noises and outliers in the data set do not affect the probability models significantly; the input features can be extracted in probability forms.
