Heterogeneous ensemble-based spike-driven few-shot online learning
Spiking neural networks (SNNs) are regarded as a promising candidate to deal with the
major challenges of current machine learning techniques, including the high energy …
major challenges of current machine learning techniques, including the high energy …
Asymmetric CNN for image superresolution
Deep convolutional neural networks (CNNs) have been widely applied for low-level vision
over the past five years. According to the nature of different applications, designing …
over the past five years. According to the nature of different applications, designing …
Effective and efficient community search over large heterogeneous information networks
Recently, the topic of community search (CS) has gained plenty of attention. Given a query
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …
Defending graph convolutional networks against dynamic graph perturbations via bayesian self-supervision
In recent years, plentiful evidence illustrates that Graph Convolutional Networks (GCNs)
achieve extraordinary accomplishments on the node classification task. However, GCNs …
achieve extraordinary accomplishments on the node classification task. However, GCNs …
Hyperspectral image denoising via matrix factorization and deep prior regularization
B Lin, X Tao, J Lu - IEEE Transactions on Image Processing, 2019 - ieeexplore.ieee.org
Deep learning has been successfully introduced for 2D-image denoising, but it is still
unsatisfactory for hyperspectral image (HSI) denoising due to the unacceptable …
unsatisfactory for hyperspectral image (HSI) denoising due to the unacceptable …
Unimodal regularized neuron stick-breaking for ordinal classification
This paper targets for the ordinal regression/classification, which objective is to learn a rule
to predict labels from a discrete but ordered set. For instance, the classification for medical …
to predict labels from a discrete but ordered set. For instance, the classification for medical …
Application of artificial intelligence in diagnosis of craniopharyngioma
Craniopharyngioma is a congenital brain tumor with clinical characteristics of hypothalamic-
pituitary dysfunction, increased intracranial pressure, and visual field disorder, among other …
pituitary dysfunction, increased intracranial pressure, and visual field disorder, among other …
Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties
Polymer electrolytes are promising candidates for the next generation lithium-ion battery
technology. Large scale screening of polymer electrolytes is hindered by the significant cost …
technology. Large scale screening of polymer electrolytes is hindered by the significant cost …