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Category:All HeadlinesWorld & GeopoliticsMarkets & EconomyTech & AIPoliticsSearch results for: "Dynamic graph neural netw" (30 stories)

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Epidemiology-Informed Graph Neural Networks for Predicting and Interpreting Transmissible Hospital-Acquired Infections: A Retrospective Cohort and Simulation Study
Lead StorymedRxivgeneral
May 12

Epidemiology-Informed Graph Neural Networks for Predicting and Interpreting Transmissible Hospital-Acquired Infections: A Retrospective Cohort and Simulation Study

<a href="https://news.google.com/rss/articles/CBMifEFVX3lxTE5YcmQtOTFMNXF0RUtmSDgwWjR2cWhkWFVGQU13bzJMSjdwcjZ2TG41Ykd4bHJFNkM3bTFfV2JJeWE4eldiRTQ5LU9Za3BpWjBfUnJTMVp6eDE2d0pBT1lZQjNjUl9LbDJ5bUU4SGdjQVpZcHpKSVJjZ212Tjk?oc=5" target="_blank">Epidemiology-Informed Graph Neural Networks for Predicting and Interpreting Transmissible Hospital-Acquired Infections: A Retrospective Cohort and Simulation Study</a>  <font color="#6f6f6f">medRxiv</font>

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Search Results for "Dynamic graph neural netw"

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29 stories displayed
STR-GNN: stability-regularized graph neural networks for suppressing spurious temporal variations in dynamic community detection
Natureworld

STR-GNN: stability-regularized graph neural networks for suppressing spurious temporal variations in dynamic community detection

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5mOHN3MFlpVTZGX1RuT3VUVlpuUnZrNWVBSktUb2hLSUpDQlRXTG1SejFwLVcyWUJJZUp3S2JPWWZqbFZHeWw3d3RZMG1laGJna2x6MjBkQVZHSWFQYzRZ?oc=5" target="_blank">STR-GNN: stability-regularized graph neural networks for suppressing spurious temporal variations in dynamic community detection</a>  <font color="#6f6f6f">Nature</font>

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Real-time dynamic graph learning with temporal attention for financial fraud detection
Frontiersgeneral

Real-time dynamic graph learning with temporal attention for financial fraud detection

<a href="https://news.google.com/rss/articles/CBMiogFBVV95cUxNRzlRWGx1aHpOdUlZeU9tTExwUFdrb1VGQkw2bGhoYjdWMDUxY3VYVDB2bWw2bTN4QWVjM1VCTTI0N0czaGVjRUxrQ3E0dHRndVI0eEJndmxRYTNpT3lBRFExLVhZR08zRTEwNzJWeVpwc2xLMzU3cFVFYkd5VVFzeDNUc1oyX0pxTndkRDdhdVRvbGlGckFzc3NOam00dWpIbFE?oc=5" target="_blank">Real-time dynamic graph learning with temporal attention for financial fraud detection</a>  <font color="#6f6f6f">Frontiers</font>

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Graph2Video: Leveraging Video Models to Model Dynamic Graph Evolution
The Association for the Advancement of Artificial Intelligencegeneral

Graph2Video: Leveraging Video Models to Model Dynamic Graph Evolution

<a href="https://news.google.com/rss/articles/CBMibEFVX3lxTFBuY1Zyc3EzMklVNDUxTmFzSEZYTnlUQmd4SFEtSlRNU3AzWWZaUDhsaWRQVFlzOEd1Y3lCUkE4N0lCOHBwc2ZsU0E5d3phUzNrS3g0NjlVZUNWbWY2ODJOVDh2NEo5djFXV1RPNQ?oc=5" target="_blank">Graph2Video: Leveraging Video Models to Model Dynamic Graph Evolution</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Graph convolutional network-based multi-threaded mixing Mamba transformer for traffic forecasting
ScienceDirect.comgeneral

Graph convolutional network-based multi-threaded mixing Mamba transformer for traffic forecasting

<a href="https://news.google.com/rss/articles/CBMie0FVX3lxTFAyWkRoRkpLclNaOTFPRC1WRERKNnRaTlRZRVh4dkRQOXJtekxjTDh1RVdKRFB2ZnJtVWtRV01mcUZILUVtZGI5Q01KTTk5c01QS090UEFTbzF0VEVpRjBXMlNVdXlEWXd4QTlsOGthZ080SXcweVY0TjhpOA?oc=5" target="_blank">Graph convolutional network-based multi-threaded mixing Mamba transformer for traffic forecasting</a>  <font color="#6f6f6f">ScienceDirect.com</font>

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Dynamic graph neural network-based framework to increase detection accuracy in SDN under DDOS
Natureworld

Dynamic graph neural network-based framework to increase detection accuracy in SDN under DDOS

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFA5VFA2Mnk1N0k2Z3d2aEtmUnJMUVdmWmxUdFpYTUE3alUwY1VoQXNwT1dwN3F1SklMU3U0VU1FQlVaNTlmWWJJN1FoS1NMTW5OampNcmtyVFZZRXdmTDhF?oc=5" target="_blank">Dynamic graph neural network-based framework to increase detection accuracy in SDN under DDOS</a>  <font color="#6f6f6f">Nature</font>

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TSA-HGNN: a stability-aware multi-scale temporal graph neural network for dynamic community detection
Frontiersworld

TSA-HGNN: a stability-aware multi-scale temporal graph neural network for dynamic community detection

<a href="https://news.google.com/rss/articles/CBMiogFBVV95cUxOY1Rsa1dyMWNhQ21WcE13SlNMdUNsdjhjZTBROWRkeGtlUWwwY3FvdXdsc3Bra2pvTG9fZkxrYlJIaHhVS3hYamctdThaeGRKa09ETjRtaW5CclBNQ1lmQ0U2ZEdlM1MzWXBqaENlelhxNG9DNVRhazd6SVQ0ZVctbVNiTk1VRmR6LWFIcnJPVXNDclhVUWpmQUhaYjlWOEVpN3c?oc=5" target="_blank">TSA-HGNN: a stability-aware multi-scale temporal graph neural network for dynamic community detection</a>  <font color="#6f6f6f">Frontiers</font>

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Attribute-guided Dynamic Prompt Learning for Graph Neural Networks
The Association for the Advancement of Artificial Intelligencegeneral

Attribute-guided Dynamic Prompt Learning for Graph Neural Networks

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTFBvR016WUJQOC1vVWowa1R1Z1U2U2R0RlM1N25qaXl0U3RJT08yNzZfd0thS01YT1RfLTdHaG5xaHlIR1g3X2owNHhNck5vTFpIX053eUd6WU5lekkyMlJaOXFCNmw?oc=5" target="_blank">Attribute-guided Dynamic Prompt Learning for Graph Neural Networks</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Temporal influence maximization via continuous-time graph neural networks and deep reinforcement learning
Naturegeneral

Temporal influence maximization via continuous-time graph neural networks and deep reinforcement learning

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9nZUVZc0lGbHRNWnI3TV9RZVd4Y3cxU1Z3ZUFLQkRqZ1hTWXZfVHpPdmlVMUlMcC1rT09DX01ISDRzTEY5WWdoUDhMeEdCOFloQjEtN0d2bEdSLTRxZ0hV?oc=5" target="_blank">Temporal influence maximization via continuous-time graph neural networks and deep reinforcement learning</a>  <font color="#6f6f6f">Nature</font>

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BAG: Benchmarking Anomaly Detection on Dynamic Graphs
The Association for the Advancement of Artificial Intelligencegeneral

BAG: Benchmarking Anomaly Detection on Dynamic Graphs

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE1FXzhRS0U5TnpxcEI2TDhlVHpVMmdZMGVDUldSclBqT3l3ZWxjVWpMNVE2ZVdaN0RKWS1JNm9heXNQalBUT0RaS0xDTFlJTFc0RUdsTHNacmQ0VktTd1h0WldJX3A?oc=5" target="_blank">BAG: Benchmarking Anomaly Detection on Dynamic Graphs</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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DMSTG-AD: an SDN intrusion detection method based on dynamic multi-scale spatio-temporal graph neural network
Naturegeneral

DMSTG-AD: an SDN intrusion detection method based on dynamic multi-scale spatio-temporal graph neural network

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1zTlhhb1Nqdi1RbE5NRjRZMVhPZk4zbG91YWVUY3JPZ1JQOWM0bzZyR0NEdE9hMzZzUmJFYjlTb0JRSDZnY0pfNnNLeFJ6TUdFNEw0VDhmMDB2dU9FVHRZ?oc=5" target="_blank">DMSTG-AD: an SDN intrusion detection method based on dynamic multi-scale spatio-temporal graph neural network</a>  <font color="#6f6f6f">Nature</font>

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Gaussian Uncertainty-Driven Multi-Model Fitting with Graph Neural Network
The Association for the Advancement of Artificial Intelligencetech

Gaussian Uncertainty-Driven Multi-Model Fitting with Graph Neural Network

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE5yN0stY3FYS1FZdHlDRURHT1RTNWF0Q1d6YXZYR1dPUUdiOFpEN3BUOUNNM0NzdlQ5WFFfaTZoRmJLUllEUW1iaEY5N1lwbFRQZU5uZVBRbjJhYXJJakFnRE1DYXk?oc=5" target="_blank">Gaussian Uncertainty-Driven Multi-Model Fitting with Graph Neural Network</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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ST-GNNFormer: coupling dynamic graph learning and multi-scale temporal attention for traffic flow forecasting
Naturegeneral

ST-GNNFormer: coupling dynamic graph learning and multi-scale temporal attention for traffic flow forecasting

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5qV0FKanlQX0lnbENmVFNBMG14TThtcXdoOEdXZWVfN05lQmQ2TDFKMmlDYkEtUUZuVlE4WnI1bFRMMVdtYlhTSEJ5UFJZZmJDNDR6YzVWRmJsb1Zobmx3?oc=5" target="_blank">ST-GNNFormer: coupling dynamic graph learning and multi-scale temporal attention for traffic flow forecasting</a>  <font color="#6f6f6f">Nature</font>

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Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning
The Association for the Advancement of Artificial Intelligencegeneral

Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE02YWNzVlVuQWpONVFhbUx1Zkw0bjV0T1F1XzF2eDdYY0RqcVZRODdPQ3hueUhuU0VWMWJxWHgyVW9YbzlzQTNDN082RlUtQTZxLUZLTmc4SURySm51akptaEdNZVk?oc=5" target="_blank">Towards OOD Generalization in Dynamic Graphs via Causal Invariant Learning</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Optimization of water-saving irrigation decision using dynamic spatiotemporal graph neural networks
Naturegeneral

Optimization of water-saving irrigation decision using dynamic spatiotemporal graph neural networks

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5PdkgxZlY0cG5SUGgyM2lqdHplbC1rRHo2V3VYaHVYNGlQQTlFV09ESFFRaE1hZExEOG94STh0d2hMaldfRHZBamhYTkN4NjcyZEttWUNrWUhBdk0tblVv?oc=5" target="_blank">Optimization of water-saving irrigation decision using dynamic spatiotemporal graph neural networks</a>  <font color="#6f6f6f">Nature</font>

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DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction
Naturegeneral

DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9XYl84dVI5YThMM194dWFES0NRNHA5UEpnQ09BWHI1QlU2VFlobWJXd2VrNk5Ib1FFR0Y2UDlvRmN6ck9wM09NQ1JYeUlnY2ZiV0ZsUV9RRE11ZnpvS3M0?oc=5" target="_blank">DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction</a>  <font color="#6f6f6f">Nature</font>

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M $$\vphantom{0}^2$$ DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson’s disease(PD) progression using whole-blood RNA sequencing data | Scientific Reports
Naturegeneral

M $$\vphantom{0}^2$$ DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson’s disease(PD) progression using whole-blood RNA sequencing data | Scientific Reports

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1sWTJoeThPZGdSNDQtN0FpR1NtYXlabUNySUloZTluODJhWU9PcjRjVXhLLXBPLUd5NlMwOFVCdEZkZ0FWUXY4Y0l5NEhQNDZ2RFM1RzhDdmFwMmNNREdR?oc=5" target="_blank">M $$\vphantom{0}^2$$ DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson’s disease(PD) progression using whole-blood RNA sequencing data | Scientific Reports</a>  <font color="#6f6f6f">Nature</font>

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Hierarchical semantic extraction and heterogeneous graph neural networks for event-driven time series forecasting
Naturegeneral

Hierarchical semantic extraction and heterogeneous graph neural networks for event-driven time series forecasting

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1iekdlTVNQY2gwNkhIOGxOSTJKYTE5aUR6Um9uSVpuNlh4VU55WVM1SHRyTGhDVmZzakZ5UHdIaVpkblpudmZpbUc2NEVVU0YtRkFGMzg4QWNTYWQtQW5R?oc=5" target="_blank">Hierarchical semantic extraction and heterogeneous graph neural networks for event-driven time series forecasting</a>  <font color="#6f6f6f">Nature</font>

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Dynamic low-altitude airspace partitioning and management strategy optimization based on graph neural networks and spatial cognitive constraints
Naturetech

Dynamic low-altitude airspace partitioning and management strategy optimization based on graph neural networks and spatial cognitive constraints

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1UamZnVk91dEZtaURXMjM5RmtZekhUUFhxVURMa290UnlXR081cmpLZlNEc1JOcFVLT1h5RlY0RE1UNnJfc0lsUGcwcUk3T2tLVk9ocWp4Qlo5SW5TZmFj?oc=5" target="_blank">Dynamic low-altitude airspace partitioning and management strategy optimization based on graph neural networks and spatial cognitive constraints</a>  <font color="#6f6f6f">Nature</font>

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Adaptive neighborhood aggregation graph neural network for early diagnosis of Alzheimer’s disease
Naturegeneral

Adaptive neighborhood aggregation graph neural network for early diagnosis of Alzheimer’s disease

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFBUbC1sb0FmSmRFTG1lQkxDOEUzMXZBLWVaemNkUGt2ZC1LWHhpWkw1X29lbjlDX3hyYWxpX3h5cHF0bGJtMEpnR2lCMUduRjMzWVNkRmU5Mmp3dE50WjA0?oc=5" target="_blank">Adaptive neighborhood aggregation graph neural network for early diagnosis of Alzheimer’s disease</a>  <font color="#6f6f6f">Nature</font>

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Physically-Informed Flow Matching with Graph Neural Networks for Complex Fluid Dynamics
The Association for the Advancement of Artificial Intelligencegeneral

Physically-Informed Flow Matching with Graph Neural Networks for Complex Fluid Dynamics

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE5ObUZfeXRxR1o4X1JEVHBQNm9UTEZJVndQdFBoMWVfaWhZZjcxOHJuQ1RUUGdKODRsOE9pcnVzTGVodjNNT2J4OGFXdnBlb2JMSTF6dkp3M29DQ0Z4al9UVDFfSmw?oc=5" target="_blank">Physically-Informed Flow Matching with Graph Neural Networks for Complex Fluid Dynamics</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Uncertainty-aware spatio-temporal contrastive graph neural networks for cyber financial fraud detection and risk management
Naturetech

Uncertainty-aware spatio-temporal contrastive graph neural networks for cyber financial fraud detection and risk management

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9peDctQlluVVVvSVdLUW9Wcjlva1E4VVgycEVSZ3E1ZURnVDBSTUdrQlJoSWk5Y0ZQQjI1UlhsSTRUSlh5aWt0SXprUnZKSnFLQnQ3X21MeDNrdkd2bzJn?oc=5" target="_blank">Uncertainty-aware spatio-temporal contrastive graph neural networks for cyber financial fraud detection and risk management</a>  <font color="#6f6f6f">Nature</font>

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SC-DGLA: constraint-aware pallet demand forecasting with dynamic graph and learnable lag alignment
Naturetech

SC-DGLA: constraint-aware pallet demand forecasting with dynamic graph and learnable lag alignment

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9MYjZYb01oc2MtSm1Gb2R6aUE0eWVSc1JDUGJ0YVVKMmJ3dEhJY0ZhTHpxLUFINFB5QzFXV2dhR1lxMHVhLXhNdzFKdmxNMjZJWk1QemdrMUVDUkRRcXNr?oc=5" target="_blank">SC-DGLA: constraint-aware pallet demand forecasting with dynamic graph and learnable lag alignment</a>  <font color="#6f6f6f">Nature</font>

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Dynamic graph convolution with comprehensive pruning and GNN classification for precise lymph node metastasis detection
Natureworld

Dynamic graph convolution with comprehensive pruning and GNN classification for precise lymph node metastasis detection

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5EWV9uUHBUWDVPdHM1VmplbDdTeFdvUXhkZWhSd285VjRLeWRlMG5wUXRTd1VGQ0RFMGtTUzVldkQ0SDAwSHpsRm9oNkpEbGZORVg0YmRCeXpVSkNfYTRJ?oc=5" target="_blank">Dynamic graph convolution with comprehensive pruning and GNN classification for precise lymph node metastasis detection</a>  <font color="#6f6f6f">Nature</font>

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Fine-grained causal effect estimation of learning resources via dynamic causal heterogeneous graph neural networks
Naturetech

Fine-grained causal effect estimation of learning resources via dynamic causal heterogeneous graph neural networks

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9Pb1doWTF6TEo0c2NyLWpKekJORzdmb1BwTi1XMHZUaWdfdUpBR00tbHN0OHA1UmIxSHFtRFZvbW15SEVfX0p3R2htYWZTazFDSWFHaUFSTURSRjN2WnY0?oc=5" target="_blank">Fine-grained causal effect estimation of learning resources via dynamic causal heterogeneous graph neural networks</a>  <font color="#6f6f6f">Nature</font>

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An optimized graph neural network approach for robust and explainable IoT intrusion detection against adversarial attacks
Naturetech

An optimized graph neural network approach for robust and explainable IoT intrusion detection against adversarial attacks

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5sVGoyZmFoSkxLZjlYb0tiSlFmdVhvMFhhUTJGb1ZpaDVUSXhJNkhEeG51XzhLT3M4cldhbTloeTNXWGNHejV2QXBrQXdKWWRiZmdNazA4SUZkVzNLMzNz?oc=5" target="_blank">An optimized graph neural network approach for robust and explainable IoT intrusion detection against adversarial attacks</a>  <font color="#6f6f6f">Nature</font>

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Dynamic heterogeneous graph contrastive learning for uncovering collusive financial fraud
Natureworld

Dynamic heterogeneous graph contrastive learning for uncovering collusive financial fraud

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5sNlcweDItbmhUbE1JZFlmdVlwUkxteFpTTGdnSGJrWUpWSlNLVG9qWURWdDZjUlpCNUw1dk9YeXlwc2ROU0d2WDhZMUlCMjg1bWRmc3NuNjJwUXFha0RB?oc=5" target="_blank">Dynamic heterogeneous graph contrastive learning for uncovering collusive financial fraud</a>  <font color="#6f6f6f">Nature</font>

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Unsupervised Detection of Persistent Communities in Dynamic Networks with Network Embeddings
The Association for the Advancement of Artificial Intelligenceworld

Unsupervised Detection of Persistent Communities in Dynamic Networks with Network Embeddings

<a href="https://news.google.com/rss/articles/CBMiZkFVX3lxTE1nNWh6bTBBOGRNUTNTeTlGSUU3RnhaN1U2dW1yRFoySTlyc3ZSTVg3cWhWYVY4RGZoME5UdVFydmZ0VktNaEpSWk9zTE5mbWdWbkNWd3g2aGV0bDVUd19PQ3IzQjZYdw?oc=5" target="_blank">Unsupervised Detection of Persistent Communities in Dynamic Networks with Network Embeddings</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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Graph Neural Networks: practical use cases, technical limits, and where they are going next
Mediumtech

Graph Neural Networks: practical use cases, technical limits, and where they are going next

<a href="https://news.google.com/rss/articles/CBMi3AFBVV95cUxQMVRWOXducTRFWVBzeWhaTzhUV1ZVZ1o1R2ljVjhJSG1hSlJLdWVyN3NoTi1OOFFoNWVkdUdPQ1JnZkFmd1lIWEsxVUR2N2lpVTB0RnhVNkdFTElzblpyUUM3WUV6elNMVldhTHBjYVlaWnp4N3A3bjJvVWt5VU50TjZZTHB1TzBNVkhFN1V0Q0FNMmpXTVN5Y3Y3dHdSN0Z0VDNucC16X1RKT3FZZWVqN215MjZMcEUzLXlnYUlYb3BKWXFhTkVTNktLWng2S1VseXctM2ZZTTI0UUtu?oc=5" target="_blank">Graph Neural Networks: practical use cases, technical limits, and where they are going next</a>  <font color="#6f6f6f">Medium</font>

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New Transformer Splits Static Roads From Dynamic Traffic to Sharper Forecasts
Bioengineer.orggeneral

New Transformer Splits Static Roads From Dynamic Traffic to Sharper Forecasts

<a href="https://news.google.com/rss/articles/CBMipAFBVV95cUxONkdTMzdXbGtuT0xvb0QtR19QOE5ZMU84VGNMd2ZscGNrQW9URl9NTTVreDRFU1l5cnlsLUtQWjNYbTNXQ2lMTUFnUXpNYlNKRXdXYjZrUXBONGx5ZVM0UXN4WFZ4Tmg4bUp3TjBjVGFTbnBKXy1Xc1hEbDladVkzcXhxYmdlT2xjYlpIRVZzS1prMWJwOFNzOXFmQnVTcjVHLUhEeg?oc=5" target="_blank">New Transformer Splits Static Roads From Dynamic Traffic to Sharper Forecasts</a>  <font color="#6f6f6f">Bioengineer.org</font>

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