πWide Graph Neural Network
πConference: The Eleventh International Conference on Learning Representations(ICLR 2023)
πPublish year: 2023
πStudy paper
π±Channel: @ComplexNetworkAnalysis
#paper #Graph_Neural_Network #Wide
πConference: The Eleventh International Conference on Learning Representations(ICLR 2023)
πPublish year: 2023
πStudy paper
π±Channel: @ComplexNetworkAnalysis
#paper #Graph_Neural_Network #Wide
π3
πNeural Network Optimization Based on Complex Network
Theory: A Survey
π journal: MATHEMATICS (I.F=2.3)
πPublish year: 2023
πStudy paper
π±Channel: @ComplexNetworkAnalysis
#paper #Neural_Network #Optimization #Survey
Theory: A Survey
π journal: MATHEMATICS (I.F=2.3)
πPublish year: 2023
πStudy paper
π±Channel: @ComplexNetworkAnalysis
#paper #Neural_Network #Optimization #Survey
π4β€1
π GraphVar - Brain Network Analysis - Part 1/2
π₯Free recorded tutorial on Brain Network Analysis
πΉThis is a demonstration of GraphVar and a walk through implemented functions. Brain Connectivity Toolbox.
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video #Brain_Network
π₯Free recorded tutorial on Brain Network Analysis
πΉThis is a demonstration of GraphVar and a walk through implemented functions. Brain Connectivity Toolbox.
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video #Brain_Network
YouTube
GraphVar - Brain Network Analysis - Part 1/2
This is a demonstration of GraphVar and a walk through implemented functions. Brain Connectivity Toolbox.
π2π1
πA Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
πPublish year: 2023
πStudy paper
π±Channel: @ComplexNetworkAnalysis
#paper #Privacy #Graph_Neural_Network #Attacks #Preservation #Applications #Survey
πPublish year: 2023
πStudy paper
π±Channel: @ComplexNetworkAnalysis
#paper #Privacy #Graph_Neural_Network #Attacks #Preservation #Applications #Survey
π4
π Benchmarking Graph Neural Network
π₯Free recorded tutorial on Benchmarking Graph Neural Network by Xavier Bresson, βYoshua Bengio| ICML Tutorial
π Slides of this video
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video #Graph_Neural_Network
π₯Free recorded tutorial on Benchmarking Graph Neural Network by Xavier Bresson, βYoshua Bengio| ICML Tutorial
π Slides of this video
π½ Watch
π±Channel: @ComplexNetworkAnalysis
#video #Graph_Neural_Network
SlidesLive
Xavier Bresson, Yoshua Bengio Β· Benchmarking Graph Neural Networks
π4
πGraph Neural Network and Some of GNN Applications: Everything You Need to Know
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #GNN
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #GNN
neptune.ai
Graph Neural Network and Some of GNN Applications
Explore Graph Neural Networks, from graph basics to deep learning concepts, Graph Convolutional Networks, and GNN applications.
π4
πMachine Learning Algorithms
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
Graph Database & Analytics
Machine Learning Algorithms - Graph Database & Analytics
Get an introduction to machine learning and how new graph-based machine learning algorithms can be used to better analyze and understand data.
π3
πTemporal Link Prediction: A Unified Framework, Taxonomy, and Review
πPublish year: 2023
π Study the paper
π²Channel: @ComplexNetworkAnalysis
#paper #Review #Graph #Link_Prediction
πPublish year: 2023
π Study the paper
π²Channel: @ComplexNetworkAnalysis
#paper #Review #Graph #Link_Prediction
π₯3π1
π Graph Analytics and Graph-based Machine Learning
π₯Free recorded tutorial by Dr Clair Sullivan.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #Graph #Machine_Learning
π₯Free recorded tutorial by Dr Clair Sullivan.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #Graph #Machine_Learning
YouTube
Graph Analytics and Graph-based Machine Learning
Machine learning has traditionally revolved around creating models around data that is characterized by embeddings attributed to individual observations. However, this ignores a signal that could potentially be very strong: the relationships between dataβ¦
π4
πIntroduction to Graph Machine Learning
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
huggingface.co
Introduction to Graph Machine Learning
Weβre on a journey to advance and democratize artificial intelligence through open source and open science.
π3β€1
πTowards Data-centric Graph Machine Learning: Review and Outlook
πPublish year: 2023
π Study the paper
π²Channel: @ComplexNetworkAnalysis
#paper #Review #Graph #Machine_Learning
πPublish year: 2023
π Study the paper
π²Channel: @ComplexNetworkAnalysis
#paper #Review #Graph #Machine_Learning
π2
Forwarded from Bioinformatics
πGraph Visualization: Alternative Models Inspired by Bioinformatics
π Journal: Sensors (I.F=3.9)
πPublish year: 2023
π Study the paper
π²Channel: @Bioinformatics
#review #visualization
π Journal: Sensors (I.F=3.9)
πPublish year: 2023
π Study the paper
π²Channel: @Bioinformatics
#review #visualization
π2
π IEICE English Webinar "Analysis of Complex Dynamical Behavior as a Temporal Network"
π₯Free recorded course by Prof. Tohru Ikeguchi, Tokyo University of Science.
π₯In this webinar, we will discuss the analysis of time-varying complex phenomena by considering measured contact data as a temporal network. Firstly, we will introduce some of the contact data currently recorded. Then, as an elemental technique for analyzing these contact data as temporal networks, we explain the analysis method for static networks. Secondly, we explain the importance of analyzing such contact data as temporal networks. We also explain how to transform contact data into temporal networks. Thirdly, we explain the distance measure between temporal networks in order to detect and quantify system dynamics from the transformed temporal networks. Furthermore, we explain how to analyze the dynamics of the changes in the contact data by converting the temporal changes in the distance into time series signals using the classical multidimensional scaling method. Finally, we conclude the methods for analyzing contact data as a temporal networks, and discuss a future direction of network analysis.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #webinar #Graph #Network #Anaysis
π₯Free recorded course by Prof. Tohru Ikeguchi, Tokyo University of Science.
π₯In this webinar, we will discuss the analysis of time-varying complex phenomena by considering measured contact data as a temporal network. Firstly, we will introduce some of the contact data currently recorded. Then, as an elemental technique for analyzing these contact data as temporal networks, we explain the analysis method for static networks. Secondly, we explain the importance of analyzing such contact data as temporal networks. We also explain how to transform contact data into temporal networks. Thirdly, we explain the distance measure between temporal networks in order to detect and quantify system dynamics from the transformed temporal networks. Furthermore, we explain how to analyze the dynamics of the changes in the contact data by converting the temporal changes in the distance into time series signals using the classical multidimensional scaling method. Finally, we conclude the methods for analyzing contact data as a temporal networks, and discuss a future direction of network analysis.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #webinar #Graph #Network #Anaysis
YouTube
IEICE English Webinar "Analysis of Complex Dynamical Behavior as a Temporal Network"
IEICE English Webinar Distinguished Lecturer Program Series July 2023
Analysis of Complex Dynamical Behavior as a Temporal Network
Lecturer: Prof. Tohru Ikeguchi, Tokyo University of Science
Biography:
Professor Tohru Ikeguchi received B.E., M.E., and Doctorβ¦
Analysis of Complex Dynamical Behavior as a Temporal Network
Lecturer: Prof. Tohru Ikeguchi, Tokyo University of Science
Biography:
Professor Tohru Ikeguchi received B.E., M.E., and Doctorβ¦
π4β€1
πGraph Machine Learning: An Overview
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
Medium
Graph Machine Learning: An Overview
Key concepts for getting started
β€4π1
πGraph Clustering with Graph Neural Networks
πPublish year: 2023
π Study the paper
π²Channel: @ComplexNetworkAnalysis
#paper #GNN #Clustering
πPublish year: 2023
π Study the paper
π²Channel: @ComplexNetworkAnalysis
#paper #GNN #Clustering
π4β€1
πVisibility graph analysis for brain: scoping review
π journal: Frontiers in Neuroscience (I.F=5.152)
πPublish year: 2023
πStudy paper
π²Channel: @ComplexNetworkAnalysis
#paper #graph #brain #review
π journal: Frontiers in Neuroscience (I.F=5.152)
πPublish year: 2023
πStudy paper
π²Channel: @ComplexNetworkAnalysis
#paper #graph #brain #review
β€3π1
πMachine Learning Algorithms
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
π₯Technical paper
π Study
π²Channel: @ComplexNetworkAnalysis
#paper #Graph #Machine_learning
Graph Database & Analytics
Machine Learning Algorithms - Graph Database & Analytics
Get an introduction to machine learning and how new graph-based machine learning algorithms can be used to better analyze and understand data.
π3