📄Introducing TensorFlow Graph Neural Networks
💥Technical Paper
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#paper #Graph #code #TensorFlow #python
💥Technical Paper
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph #code #TensorFlow #python
blog.tensorflow.org
Introducing TensorFlow Graph Neural Networks
Introducing TensorFlow GNN, a library to build Graph Neural Networks on the TensorFlow
platform.
platform.
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📄Graph-Based Data Science, Machine Learning, and AI
💥Technical Paper
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph #AI #Data_Science #Machine_Learning
💥Technical Paper
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph #AI #Data_Science #Machine_Learning
DZone
Graph-Based Data Science, Machine Learning, and AI
What does graphing have to do with machine learning and data science? A lot, actually — learn more in The Year of the Graph Newsletter's Spring 2021 edition.
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📃 Recommendation Systems for Education: Systematic Review
📘 Journal: Electronics (I.F=2.9)
🗓 Publish year: 2021
🧑💻Authors: María Cora Urdaneta-Ponte, Amaia Mendez-Zorrilla, Ibon Oleagordia-Ruiz
🏢Universities: University of Deusto, Andres Bello Catholic University (UCAB)
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#paper #Recommender_Systems #Education #review
📘 Journal: Electronics (I.F=2.9)
🗓 Publish year: 2021
🧑💻Authors: María Cora Urdaneta-Ponte, Amaia Mendez-Zorrilla, Ibon Oleagordia-Ruiz
🏢Universities: University of Deusto, Andres Bello Catholic University (UCAB)
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📱Channel: @ComplexNetworkAnalysis
#paper #Recommender_Systems #Education #review
👍3
🔊 Important Reminder:
💥 Deadline Approaching for
📓 "Advances in Graph-Based Data Mining" Special Issue
🔶Topics:
▫️graph-based data mining
▫️network analysis
▫️graph algorithms
▫️graph neural networks
▫️community detection
▫️complex data relationships
▫️knowledge extraction
🌐 More information & Submission
📲Channel: @ComplexNetworkAnalysis
#journal #special_issue
💥 Deadline Approaching for
📓 "Advances in Graph-Based Data Mining" Special Issue
🔶Topics:
▫️graph-based data mining
▫️network analysis
▫️graph algorithms
▫️graph neural networks
▫️community detection
▫️complex data relationships
▫️knowledge extraction
🌐 More information & Submission
📲Channel: @ComplexNetworkAnalysis
#journal #special_issue
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📃 A social network of crime: A review of the use of social networks for crime and the detection of crime
📘 Journal: Online Social Networks and Media (I.F=7.61)
🗓 Publish year: 2024
🧑💻Authors: Brett Drury, Samuel Morais Drury, Md Arafatur Rahman, Ihsan Ullah
🏢Universities: National University of Ireland Galway, University College Dublin, Liverpool Hope University, University Malaysia Pahang
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📲Channel: @ComplexNetworkAnalysis
#paper #crime #social_network #Review
📘 Journal: Online Social Networks and Media (I.F=7.61)
🗓 Publish year: 2024
🧑💻Authors: Brett Drury, Samuel Morais Drury, Md Arafatur Rahman, Ihsan Ullah
🏢Universities: National University of Ireland Galway, University College Dublin, Liverpool Hope University, University Malaysia Pahang
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📲Channel: @ComplexNetworkAnalysis
#paper #crime #social_network #Review
👍4
📃 Social search: Retrieving information in Online Social platforms – A survey
📘 Journal: Online Social Networks and Media
🗓 Publish year: 2023
🧑💻Authors: Maddalena Amendola, Andrea Passarella, Raffaele Perego
🏢University: University of Pisa
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#paper #Social #Retrieving_information #survey
📘 Journal: Online Social Networks and Media
🗓 Publish year: 2023
🧑💻Authors: Maddalena Amendola, Andrea Passarella, Raffaele Perego
🏢University: University of Pisa
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#paper #Social #Retrieving_information #survey
👍5
🎞 Machine Learning with Graphs: Graph Neural Networks in Computational Biology
💥Free recorded course by Prof. Marinka Zitnik
💥In this lecture, Prof. Marinka gives an overview of why graph learning techniques can greatly help with computational biology research. Concretely, this talk covers 3 exemplar use cases: (1) Discovering safe drug-drug combinations via multi-relational link prediction on heterogenous knowledge graphs; (2) Classify patient outcomes and diseases via learning subgraph embeddings; and (3) Learning effective disease treatments through few-shot learning for graphs.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning #computational_biology
💥Free recorded course by Prof. Marinka Zitnik
💥In this lecture, Prof. Marinka gives an overview of why graph learning techniques can greatly help with computational biology research. Concretely, this talk covers 3 exemplar use cases: (1) Discovering safe drug-drug combinations via multi-relational link prediction on heterogenous knowledge graphs; (2) Classify patient outcomes and diseases via learning subgraph embeddings; and (3) Learning effective disease treatments through few-shot learning for graphs.
📽 Watch
📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning #computational_biology
YouTube
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 18 - GNNs in Computational Biology
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/2XVImFC
Lecture 18 - Graph Neural Networks in Computational Biology
Jure Leskovec
Computer Science, PhD
We are glad to invite Prof.…
Lecture 18 - Graph Neural Networks in Computational Biology
Jure Leskovec
Computer Science, PhD
We are glad to invite Prof.…
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🎓Study of Tensor Network Applications in Complex Networks
📘Integrated master's thesis in engineering physics
🗓Publish year: 2022
📎Study Thesis
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#Thesis #Tensor_Networks #Application
📘Integrated master's thesis in engineering physics
🗓Publish year: 2022
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#Thesis #Tensor_Networks #Application
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📃Data-centric Graph Learning: A Survey
📘 Journal: JOURNAL OF LATEX CLASS FILES
🗓 Publish year: 2021
🧑💻Authors: Yuxin Guo, Deyu Bo, Cheng Yang, Zhiyuan Lu, Zhongjian Zhang, Jixi Liu, Yufei Peng, Chuan Shi
🏢Universities: Beijing University of Posts and Telecommunications
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📲Channel: @ComplexNetworkAnalysis
#paper #crime #Graph_Learning #Survey
📘 Journal: JOURNAL OF LATEX CLASS FILES
🗓 Publish year: 2021
🧑💻Authors: Yuxin Guo, Deyu Bo, Cheng Yang, Zhiyuan Lu, Zhongjian Zhang, Jixi Liu, Yufei Peng, Chuan Shi
🏢Universities: Beijing University of Posts and Telecommunications
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📲Channel: @ComplexNetworkAnalysis
#paper #crime #Graph_Learning #Survey
👏2
📃Comprehensive evaluation of deep and graph learning on drug–drug interactions prediction
📘 Journal: Briefings in Bioinformatics(I.F=13.994)
🗓 Publish year: 2023
🧑💻Authors: Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S Yu, Xiangxiang Zeng
🏢Universities: Xiangtan University, Huazhong Agricultural University, Hunan University,
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📲Channel: @ComplexNetworkAnalysis
#paper #drug_drug_interactions #Graph_Learning #deep_learning #prediction
📘 Journal: Briefings in Bioinformatics(I.F=13.994)
🗓 Publish year: 2023
🧑💻Authors: Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen, Bosheng Song, Philip S Yu, Xiangxiang Zeng
🏢Universities: Xiangtan University, Huazhong Agricultural University, Hunan University,
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#paper #drug_drug_interactions #Graph_Learning #deep_learning #prediction
👍2❤1
📃 A review of Graph Neural Networks for Electroencephalography data analysis
📘 Journal: Neurocomputing (I.F=6)
🗓 Publish year: 2023
🧑💻Authors: Manuel Graña, Igone Morais-Quilez
🏢University: University of the Basque Country (UPV/EHU), San Sebastian, Spain
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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Electroencephalography #review
📘 Journal: Neurocomputing (I.F=6)
🗓 Publish year: 2023
🧑💻Authors: Manuel Graña, Igone Morais-Quilez
🏢University: University of the Basque Country (UPV/EHU), San Sebastian, Spain
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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Electroencephalography #review
👍2
📕Handbook on Biological networks
✨Networks at the Cellular Level
-The Structural Network Properties of Biological Systems (M Brilli & P Lió)
-Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.)
-Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert)
-Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A Díaz-Guilera & R Álvarez-Buylla)
-Geometry and Topology of Folding Landscapes (L Bongini & L Casetti)
-Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.)
-Metabolic Networks (M C Palumbo et al.)
✨Brain Networks:
-The Human
Brain Network (O Sporns)
-Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni)
-An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.)
-Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.)
-Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme)
✨Networks at the Individual and Population Levels:
-Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.)
-Evolutionary Models for Simple Biosystems (F Bagnoli)
-Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.)
-From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.)
-Interplay of Network State and Topology in Epidemic Dynamics (T Gross)
🌐 Read online
📲Channel: @ComplexNetworkAnalysis
#Handbook #Biological
✨Networks at the Cellular Level
-The Structural Network Properties of Biological Systems (M Brilli & P Lió)
-Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.)
-Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert)
-Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A Díaz-Guilera & R Álvarez-Buylla)
-Geometry and Topology of Folding Landscapes (L Bongini & L Casetti)
-Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.)
-Metabolic Networks (M C Palumbo et al.)
✨Brain Networks:
-The Human
Brain Network (O Sporns)
-Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni)
-An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.)
-Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.)
-Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme)
✨Networks at the Individual and Population Levels:
-Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.)
-Evolutionary Models for Simple Biosystems (F Bagnoli)
-Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.)
-From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.)
-Interplay of Network State and Topology in Epidemic Dynamics (T Gross)
🌐 Read online
📲Channel: @ComplexNetworkAnalysis
#Handbook #Biological
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📃Multilayer Clustered Graph Learning
🗓 Publish year: 2020
🧑💻Authors: Mireille El Gheche, Pascal Frossard
🏢Universities: Ecole Polytechnique Fed´ erale de Lausanne (EPFL)
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#paper #Graph_Learning #Multilayer_graph
🗓 Publish year: 2020
🧑💻Authors: Mireille El Gheche, Pascal Frossard
🏢Universities: Ecole Polytechnique Fed´ erale de Lausanne (EPFL)
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Learning #Multilayer_graph
👍3
📃SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning
🗓 Publish year: 2023
🧑💻Authors: Keyu Duan, Qian Liu,Tat-Seng Chua, Shuicheng Yan, Wei Tsang Ooi, Qizhe Xie, Junxian He
🏢Universities: ENational University of Singapore, The Hong Kong University of Science and Technology
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💻 Code
📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Learning #Textual
🗓 Publish year: 2023
🧑💻Authors: Keyu Duan, Qian Liu,Tat-Seng Chua, Shuicheng Yan, Wei Tsang Ooi, Qizhe Xie, Junxian He
🏢Universities: ENational University of Singapore, The Hong Kong University of Science and Technology
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💻 Code
📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Learning #Textual
👏3
📃 A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
🗓 Publish year: 2024
🧑💻Authors: Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang
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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Imbalance #Noise #Privacy #OOD_Challenges #Survey
🗓 Publish year: 2024
🧑💻Authors: Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang
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📱Channel: @ComplexNetworkAnalysis
#paper #GNN #Imbalance #Noise #Privacy #OOD_Challenges #Survey
👍1
📃Graph Condensation: A Survey
🗓 Publish year: 2023
🧑💻Authors: Xinyi Gao, Junliang Yu, Wei Jiang, Tong Chen, Wentao Zhang, Hongzhi Yin
🏢Universities: The University of Queensland, Peking University
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Condensation #Survey
🗓 Publish year: 2023
🧑💻Authors: Xinyi Gao, Junliang Yu, Wei Jiang, Tong Chen, Wentao Zhang, Hongzhi Yin
🏢Universities: The University of Queensland, Peking University
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph_Condensation #Survey
👍3
📃A Survey on Knowledge Editing of Neural Networks
🗓 Publish year: 2023
🧑💻Authors: Vittorio Mazzia, Alessandro Pedrani, Andrea Caciolai, Kay Rottmann, Davide Bernardi
🏢Universities: Amazon
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📲Channel: @ComplexNetworkAnalysis
#paper #Survey #Knowledge #Neural_Networks
🗓 Publish year: 2023
🧑💻Authors: Vittorio Mazzia, Alessandro Pedrani, Andrea Caciolai, Kay Rottmann, Davide Bernardi
🏢Universities: Amazon
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📲Channel: @ComplexNetworkAnalysis
#paper #Survey #Knowledge #Neural_Networks
👍2
Forwarded from Bioinformatics
📑 Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine
📗Journal: Briefings in Bioinformatics (I.F.= 9.5)
🗓 Publish year: 2024
🧑💻Authors: Peng Zhang, Dingfan Zhang, Wuai Zhou, ...
🏢University: Tsinghua University, China
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📲Channel: @Bioinformatics
#review #pharmacology #network #ai #medicine
📗Journal: Briefings in Bioinformatics (I.F.= 9.5)
🗓 Publish year: 2024
🧑💻Authors: Peng Zhang, Dingfan Zhang, Wuai Zhou, ...
🏢University: Tsinghua University, China
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📲Channel: @Bioinformatics
#review #pharmacology #network #ai #medicine
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