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Found 12 papers, 2 papers with code
Weighted Graph Structure Learning with Attention Denoising for Node Classification
EWGSL improves node classification by redefining attention coefficients in graph attention networks to incorporate node features and edge weights.
Time-Graph Frequency Representation with Singular Value Decomposition for Neural Speech Enhancement
However, most methods suffer from the alignment modeling of amplitude and phase (real and imaginary pairs) in a two-stream network framework, which inevitably incurs performance restrictions.
A Comprehensive Survey on Root Cause Analysis in (Micro) Services: Methodologies, Challenges, and Trends
The complex dependencies and propagative faults inherent in microservices, characterized by a dense network of interconnected services, pose significant challenges in identifying the underlying causes of issues.
Incorporating Higher-order Structural Information for Graph Clustering
In recent years, graph convolutional network (GCN) has emerged as a powerful tool for deep clustering, integrating both graph structural information and node attributes.
KGroot: Enhancing Root Cause Analysis through Knowledge Graphs and Graph Convolutional Neural Networks
To achieve this, KGroot uses event knowledge and the correlation between events to perform root cause reasoning by integrating knowledge graphs and GCNs for RCA.
Three-Stage Cascade Framework for Blurry Video Frame Interpolation
Besides, experiments on real-world blurry videos also indicate the good generalization ability of our model.
LostNet: A smart way for lost and find
Due to the enormous population growth of cities in recent years, objects are frequently lost and unclaimed on public transportation, in restaurants, or any other public areas.
Universal Graph Filter Design based on Butterworth, Chebyshev and Elliptic Functions
In this paper, we propose to design universal IIR graph filters with low computational complexity by using three kinds of functions, which are Butterworth, Chebyshev, and Elliptic functions, respectively.
Optimal Fractional Fourier Filtering in Time-vertex Graphs signal processing
Furthermore, the optimal time-vertex graph filter in fractional domains is also developed, using the graph fractional Laplacian operator and graph fractional Fourier transform.
Web-Scale Generic Object Detection at Microsoft Bing
In this paper, we present Generic Object Detection (GenOD), one of the largest object detection systems deployed to a web-scale general visual search engine that can detect over 900 categories for all Microsoft Bing Visual Search queries in near real-time.
A survey on natural language processing (nlp) and applications in insurance
It brings today, many opportunities for the insurance industry. Understanding those methods and, above all, knowing how to apply them is a major challenge and key to unleash the value of text data that have been stored for many years.
An Iterative Graph Spectral Subtraction Method for Speech Enhancement
In this paper, we investigate the application of graph signal processing (GSP) theory in speech enhancement.
