📄Deep Learning for Community Detection: Progress, Challenges and Opportunities
📘Conference: Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}
🗓Publish year: 2020
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#paper #CommunityDetection #DeepLearning
📘Conference: Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}
🗓Publish year: 2020
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📲Channel: @ComplexNetworkAnalysis
#paper #CommunityDetection #DeepLearning
📄Graph neural networks: A review of methods and applications
📘Journal: AI Open
🗓Publish year: 2020
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📱Channel: @ComplexNetworkAnalysis
#paper #review #applications
📘Journal: AI Open
🗓Publish year: 2020
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📱Channel: @ComplexNetworkAnalysis
#paper #review #applications
📄Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic
📘Journal: International Statistical Institute (I.F=1.946)
🗓Publish year: 2020
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📱Channel: @ComplexNetworkAnalysis
#paper #review #Applications #Coronavirus
📘Journal: International Statistical Institute (I.F=1.946)
🗓Publish year: 2020
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📱Channel: @ComplexNetworkAnalysis
#paper #review #Applications #Coronavirus
📄A Review of Graph and Network Complexity from an Algorithmic Information Perspective
📘Journal: Entropy (I.F=2.738)
🗓Publish year: 2018
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📱Channel: @ComplexNetworkAnalysis
#paper #review
📘Journal: Entropy (I.F=2.738)
🗓Publish year: 2018
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📱Channel: @ComplexNetworkAnalysis
#paper #review
📄Bipartite Graphs as Models of Complex Networks
🗓Publish year: 2021
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📲Channel: @ComplexNetworkAnalysis
#paper
🗓Publish year: 2021
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📲Channel: @ComplexNetworkAnalysis
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📄Community Detection Algorithms
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper #CommunityDetection
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
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Medium
Community Detection Algorithms
Many of you are familiar with networks, right? You might be using social media sites such as Facebook, Instagram, Twitter, etc. They are…
📄A Review on Graph Theory in Network and Artificial Intelligence
📘Conference: International Conference on Robotics and Artificial Intelligence (RoAI) 2020 28-29 December 2020, Chennai, India
🗓Publish year: 2021
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📱Channel: @ComplexNetworkAnalysis
#paper #review #Artificial_Intelligence
📘Conference: International Conference on Robotics and Artificial Intelligence (RoAI) 2020 28-29 December 2020, Chennai, India
🗓Publish year: 2021
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📱Channel: @ComplexNetworkAnalysis
#paper #review #Artificial_Intelligence
🎞 Modeling epidemics on complex networks
💥Free recorded Lecture in Department of Computer Science IIL Ropar
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📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture in Department of Computer Science IIL Ropar
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📲Channel: @ComplexNetworkAnalysis
#video #Lecture
YouTube
Modeling epidemics on complex networks
📄Community Detection Methods in Social Network Analysis
📘Journal: Journal of Computational and Theoretical Nanoscience (I.F=0.488)
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#paper #CommunityDetection
📘Journal: Journal of Computational and Theoretical Nanoscience (I.F=0.488)
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#paper #CommunityDetection
🎞 Multi-agent models in complex networks
💥Free recorded Lecture by Pablo Balenzuela (University of Buenos Aires, Argentina)
📽 Watch: part1 part2 part3 part4
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture by Pablo Balenzuela (University of Buenos Aires, Argentina)
📽 Watch: part1 part2 part3 part4
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
YouTube
Multi-agent models in complex networks (1 o 4)
Preparatory School for StatPhys 2019
July 1-5, 2019
Introduction to nonlinear dynamics
Speaker:
Pablo Balenzuela (University of Buenos Aires, Argentina)
More informations: https://www.ictp-saifr.org/preparatory-school-for-statphys-2019/
July 1-5, 2019
Introduction to nonlinear dynamics
Speaker:
Pablo Balenzuela (University of Buenos Aires, Argentina)
More informations: https://www.ictp-saifr.org/preparatory-school-for-statphys-2019/
👍2
📄Implement Louvain Community Detection Algorithm using Python and Gephi with visualization
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper #CommunityDetection #Gephi #Louvain #code #python
💥Technical paper
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#paper #CommunityDetection #Gephi #Louvain #code #python
Medium
Implement Louvain Community Detection Algorithm using Python and Gephi with visualization
Louvain Community Detection Algorithm
👍1
🎞 Introduction to Static Complex Networks
💥Free recorded course by Professor Stephen Lansing
💥This course explores the features of complexity science. Our world is connected by an abundance of complex systems. Across all levels of organizations from physical, biological world to the social world, we may think of the connectivity between individual elements and how they interact and influence each other. For example, how humans transmit pandemics within a group, how cars interact in the traffic system and how networks connect in governmental organizations. Although these systems are diverse and different, they have surprisingly huge features in common. In the past several decades, the study of complexity science has been increasing. It is widely acknowledged that an innovative, integrated and analytical way of thinking is essential for understanding the complex issues in the human societies. In this course, we will aim to give everyone a comprehensive introduction of the complex systems, to talk about the resilience, robustness and sustainability of the systems and to learn basic mathematical methods for complex system analysis, for example regime shifts and tipping points, the agent-based modelling, the dynamic and network theories. Most importantly, we will implement the theories into practical applications of cities and health to help students gain practice in complex systems way of thinking.
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📲Channel: @ComplexNetworkAnalysis
#video #course
💥Free recorded course by Professor Stephen Lansing
💥This course explores the features of complexity science. Our world is connected by an abundance of complex systems. Across all levels of organizations from physical, biological world to the social world, we may think of the connectivity between individual elements and how they interact and influence each other. For example, how humans transmit pandemics within a group, how cars interact in the traffic system and how networks connect in governmental organizations. Although these systems are diverse and different, they have surprisingly huge features in common. In the past several decades, the study of complexity science has been increasing. It is widely acknowledged that an innovative, integrated and analytical way of thinking is essential for understanding the complex issues in the human societies. In this course, we will aim to give everyone a comprehensive introduction of the complex systems, to talk about the resilience, robustness and sustainability of the systems and to learn basic mathematical methods for complex system analysis, for example regime shifts and tipping points, the agent-based modelling, the dynamic and network theories. Most importantly, we will implement the theories into practical applications of cities and health to help students gain practice in complex systems way of thinking.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course
Coursera
Introduction to Static Complex Networks (Part I) - Professor Stephen Lansing - Week 5: Introduction to Static Complex Network |…
Video created by Nanyang Technological University, ...
📄Graph Neural Networks: a bibliometrics overview
📘Journal: Machine Learning with Applications (MLWA)
🗓Publish year: 2022
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📱Channel: @ComplexNetworkAnalysis
#paper #overview
📘Journal: Machine Learning with Applications (MLWA)
🗓Publish year: 2022
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📱Channel: @ComplexNetworkAnalysis
#paper #overview
📄The Co-authorship Network of Published Articles in Conferences on Web Research Based on Social Network Analysis
📘Journal: International Journal on Web Research (IJWR)
🗓Publish year: 2020
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📱Channel: @ComplexNetworkAnalysis
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📘Journal: International Journal on Web Research (IJWR)
🗓Publish year: 2020
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#paper #Co_authorship_Network
🎞 Complex Networks, Simple Rules
💥Free recorded Lecture
💥Complex networks are all around us, and they can be generated by simple mechanisms. Understanding what kinds of networks can be produced by following simple rules is therefore of great importance. We investigate this issue by studying the dynamics of extremely simple systems where are `writer' moves around a network, and modifies it in a way that depends upon the writer's surroundings. Each vertex in the network has three edges incident upon it, which are colored red, blue and green.
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📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture
💥Complex networks are all around us, and they can be generated by simple mechanisms. Understanding what kinds of networks can be produced by following simple rules is therefore of great importance. We investigate this issue by studying the dynamics of extremely simple systems where are `writer' moves around a network, and modifies it in a way that depends upon the writer's surroundings. Each vertex in the network has three edges incident upon it, which are colored red, blue and green.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
🎞 Complex networks of time-series: what does it reveal more than local interactions?
💥Free recorded Lecture by Amirhossein Shirazi, IFISC (UIB-CSIC)
💥There is a huge literature about extracting the interaction network of these systems in molecular biology, neuroscience and economy. Although this approach invigorates these disciplines to deal with large data, it usually focuses on microscopic results. In this presentation, I will suggest some holistic approaches towards the analysis of these networks, based on two examples: medical words network evolution and stock market network near the crisis. Finally, I will try to connect the measured global indicators to dynamics of the system, using the idea of symmetry breaking in the spin glass models.
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📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture by Amirhossein Shirazi, IFISC (UIB-CSIC)
💥There is a huge literature about extracting the interaction network of these systems in molecular biology, neuroscience and economy. Although this approach invigorates these disciplines to deal with large data, it usually focuses on microscopic results. In this presentation, I will suggest some holistic approaches towards the analysis of these networks, based on two examples: medical words network evolution and stock market network near the crisis. Finally, I will try to connect the measured global indicators to dynamics of the system, using the idea of symmetry breaking in the spin glass models.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
YouTube
Complex networks of time-series: what does it reveal more than local interactions?
- By: Amirhossein Shirazi, IFISC (UIB-CSIC)
- Date: 2015-09-24 14:30:00
- Denoscription: In many complex systems, the only observable variables are the time-series and event-series of their components. There is a huge literature about extracting the interaction…
- Date: 2015-09-24 14:30:00
- Denoscription: In many complex systems, the only observable variables are the time-series and event-series of their components. There is a huge literature about extracting the interaction…
📄Network Controllability Is Determined by the Density of Low In-Degree and Out-Degree Nodes
🗓Publish year: 2014
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#paper #NetworkControllability
🗓Publish year: 2014
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📲Channel: @ComplexNetworkAnalysis
#paper #NetworkControllability
📄Characterizing cycle structure in complex networks
📘Journal: Communications Physics (I.F=6.497)
🗓Publish year: 2021
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📘Journal: Communications Physics (I.F=6.497)
🗓Publish year: 2021
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#paper
📄A guide to choosing and implementing reference models for social network analysis
📘Journal: BIOLOGICAL REVIEWS (I.F=14.35)
🗓Publish year: 2021
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📱Channel: @ComplexNetworkAnalysis
#paper #implementing
📘Journal: BIOLOGICAL REVIEWS (I.F=14.35)
🗓Publish year: 2021
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📱Channel: @ComplexNetworkAnalysis
#paper #implementing
🎞 The Structure of Complex Networks: Scale-Free and Small-World Random Graphs
💥Free recorded Lecture by Remco van der Hofstad
💥In this lecture for a broad audience, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modeling in terms of graphs and how real-world networks can be modeled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion and competition on such networks.
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📲Channel: @ComplexNetworkAnalysis
#video #Lecture
💥Free recorded Lecture by Remco van der Hofstad
💥In this lecture for a broad audience, we describe a few real-world networks and some of their empirical properties. We also describe the effectiveness of abstract network modeling in terms of graphs and how real-world networks can be modeled, as well as how these models help us to give sense to the empirical findings. We continue by discussing some random graph models for real-world networks and their properties, as well as their merits and flaws as network models. We conclude by discussing the implications of some of the empirical findings on information diffusion and competition on such networks.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #Lecture
YouTube
Remco van der Hofstad - The Structure of Complex Networks: Scale-Free and Small-World Random Graphs
Abstract:
Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks.
Many large-scale networks…
Many phenomena in the real world can be phrased in terms of networks. Examples include the World-Wide Web, social interactions and Internet, but also the interaction patterns between proteins, food webs and citation networks.
Many large-scale networks…