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Found 8 papers, 2 papers with code
GNN-Ensemble: Towards Random Decision Graph Neural Networks
In the meantime, we show that GNN-Ensemble can significantly improve the adversarial robustness against attacks on GNNs.
Towards a New Science of Disinformation
How can we best address the dangerous impact that deep learning-generated fake audios, photographs, and videos (a. k. a.
Dual-view Snapshot Compressive Imaging via Optical Flow Aided Recurrent Neural Network
In this paper, we propose an optical flow-aided recurrent neural network for dual video SCI systems, which provides high-quality decoding in seconds.
Factorized Discriminant Analysis for Genetic Signatures of Neuronal Phenotypes
Navigating the complex landscape of single-cell transcriptomic data presents significant challenges.
Factorized linear discriminant analysis for phenotype-guided representation learning of neuronal gene expression data
A central goal in neurobiology is to relate the expression of genes to the structural and functional properties of neuronal types, collectively called their phenotypes.
Temporal Tensor Transformation Network for Multivariate Time Series Prediction
In this work, we present a novel deep learning architecture, known as Temporal Tensor Transformation Network, which transforms the original multivariate time series into a higher order of tensor through the proposed Temporal-Slicing Stack Transformation.
StackInsights: Cognitive Learning for Hybrid Cloud Readiness
Hybrid cloud is an integrated cloud computing environment utilizing a mix of public cloud, private cloud, and on-premise traditional IT infrastructures.
Gaussian Mixture Models with Component Means Constrained in Pre-selected Subspaces
This motivates us to find a subspace by applying weighted principal component analysis to the modes of a kernel density and the class means.
