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Category:All HeadlinesWorld & GeopoliticsMarkets & EconomyTech & AIPoliticsSearch results for: "Real-time dynamic graph l" (30 stories)

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Real-time dynamic graph learning with temporal attention for financial fraud detection
Lead StoryFrontiersgeneral
Feb 9

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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Search Results for "Real-time dynamic graph l"

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29 stories displayed
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>

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>

Spatial–Temporal Graph Learning for Taxi Origin–Destination Demand Prediction
Wiley Online Librarygeneral

Spatial–Temporal Graph Learning for Taxi Origin–Destination Demand Prediction

<a href="https://news.google.com/rss/articles/CBMiakFVX3lxTE5la0NySHhnUWNKVlhlUFo3QWRiQWt0Ymh3M1poalBqZU5Pb1VSbGRoQVVuMzVJNF9tcUNaTjhEOW93bVlhOHkxaUNscXlpa1FsOHNnVEdDTFZzRi0tMXhvakdaa2l3YkVQZkE?oc=5" target="_blank">Spatial–Temporal Graph Learning for Taxi Origin–Destination Demand Prediction</a>  <font color="#6f6f6f">Wiley Online Library</font>

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>

Physics-informed graph neural networks for real-time prediction of wall shear stress in stenotic coronary arteries
Naturegeneral

Physics-informed graph neural networks for real-time prediction of wall shear stress in stenotic coronary arteries

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE54aXJJMmVQMjc1RkZtVzdadXNPQi1wcVpSekQtVXJYTVJULU9jR3JHRHFzQTFTaG5uVEtoRmtzdXlESE1MNld1T2U2ck9sS3k2SjJJNHc0ZUlNdUYwOFRB?oc=5" target="_blank">Physics-informed graph neural networks for real-time prediction of wall shear stress in stenotic coronary arteries</a>  <font color="#6f6f6f">Nature</font>

6G conditioned spatiotemporal graph neural networks for real time traffic flow prediction
Naturegeneral

6G conditioned spatiotemporal graph neural networks for real time traffic flow prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE50R3pNdmdqQ0JIMGtOVDlCbGNId3RJSmo0Tm5IVUUxTERLM2ZHUi1qS2hYV1ViR3QtNXhpSldNNlo0cUI5OU9ub09MN1RQM1kzMWVTNzZyQmVNaGJka3VV?oc=5" target="_blank">6G conditioned spatiotemporal graph neural networks for real time traffic flow prediction</a>  <font color="#6f6f6f">Nature</font>

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>

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>

Research on traffic flow prediction based on dual-channel hybrid graph learning with trend-aware attention
Naturegeneral

Research on traffic flow prediction based on dual-channel hybrid graph learning with trend-aware attention

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9ic0pwZ1BsZ3hxbXNCQzdiTHFyX1NyeXZtVzBOZ0NCQUoxX2RXa3E0Wk9QcFhva1NmalczdERJQmZJa05Xb1YxRDRfM0wwYzdTbVR5WWRITTA3dkhQWHJj?oc=5" target="_blank">Research on traffic flow prediction based on dual-channel hybrid graph learning with trend-aware attention</a>  <font color="#6f6f6f">Nature</font>

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>

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>

Adaptable graph region for optimizing performance in dynamic system long-term forecasting via time-aware expert
Naturegeneral

Adaptable graph region for optimizing performance in dynamic system long-term forecasting via time-aware expert

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE03N2ptTzlXQTEwMTh5a3Bza1g4dWVLWm9URDA0eEY5WUhWNDUyQWZrTjVWdWZKbnNIWjRxb1pxYXVWdEYtemNUN0tRc1ZZWktXdHN6d2dNalo1RS1DV2JN?oc=5" target="_blank">Adaptable graph region for optimizing performance in dynamic system long-term forecasting via time-aware expert</a>  <font color="#6f6f6f">Nature</font>

PGSFormer: traffic flow prediction based on joint optimization of progressive graph convolutional networks with subseries transformer
Naturegeneral

PGSFormer: traffic flow prediction based on joint optimization of progressive graph convolutional networks with subseries transformer

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFA5YUQ1WUtzWFVKM0lGU2owUVZCaFZrbG9xMzd6dzZsN3NUcmhzcmkzMGZrcHdXcVN1cHYyeFd4ei05d3hNTFdMcFNOS0t4SXpSbWFiMmo2bjVKSmtuT0JB?oc=5" target="_blank">PGSFormer: traffic flow prediction based on joint optimization of progressive graph convolutional networks with subseries transformer</a>  <font color="#6f6f6f">Nature</font>

NeuroPlayNet: a multimodal AI framework for real-time cognitive-aware strategy optimization in professional basketball
Naturetech

NeuroPlayNet: a multimodal AI framework for real-time cognitive-aware strategy optimization in professional basketball

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1NU3kwVmg0R1NDTUNBVTBJYmtFUWlXZVpKaHM3cFp0QkE4OWJleml3blM0LVVSZGMzY2tuamF1S0xRTVFSSk5TOFZxbTlOenVsUEhwZDJ0TXJaMndWdUZJ?oc=5" target="_blank">NeuroPlayNet: a multimodal AI framework for real-time cognitive-aware strategy optimization in professional basketball</a>  <font color="#6f6f6f">Nature</font>

An explainable real time sensor graph transformer for dance recognition
Naturetech

An explainable real time sensor graph transformer for dance recognition

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9yaV83OGEzMU16djllWkUzcHl2SndIX01LNF9sTzZMZFh0R0ZncGptdXVmVXo1THJ2dFo5ZTcyVUx1Zmd4SXAydDJUY29YV1V6YS1CWlM1SExVTkdKakRR?oc=5" target="_blank">An explainable real time sensor graph transformer for dance recognition</a>  <font color="#6f6f6f">Nature</font>

Detecting illicit transactions in bitcoin: a wavelet-temporal graph transformer approach for anti-money laundering
Natureworld

Detecting illicit transactions in bitcoin: a wavelet-temporal graph transformer approach for anti-money laundering

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5oaE05ZnoxSUo4cllyeFFENXBxWlBWV3RCTVkxZEFvc0Z2VmhWcktLSk1yVmxJdmw5UU52RmRRMmVDM1I5Z3N4SXpyRnBtQW9LTlU3ZmVLdkhjc2Q0X0xZ?oc=5" target="_blank">Detecting illicit transactions in bitcoin: a wavelet-temporal graph transformer approach for anti-money laundering</a>  <font color="#6f6f6f">Nature</font>

FreFilterTST: a dynamic channel graph sparsification approach to multivariate time series anomaly detection with frequency-domain restoration
Naturetech

FreFilterTST: a dynamic channel graph sparsification approach to multivariate time series anomaly detection with frequency-domain restoration

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5uYzI5U3k4am5CMTd4X2FCODRDUHlsSW5oYmVteGtLYUJyaWc2MzZ6NThmeE5taS12UUZqY0NDcFo0VFdGYVJPcmlTb3YyYlpSWEIwY2UtS1FIYnhsTmFJ?oc=5" target="_blank">FreFilterTST: a dynamic channel graph sparsification approach to multivariate time series anomaly detection with frequency-domain restoration</a>  <font color="#6f6f6f">Nature</font>

DSTGA-Mamba: a disentangled spatio-temporal graph attention Mamba model for traffic flow prediction
Naturegeneral

DSTGA-Mamba: a disentangled spatio-temporal graph attention Mamba model for traffic flow prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE0wTG5LWXEwM1M1RXRDaThpSUdDc2RLZTh4cjc3WVF5WGVYM21zVUx4dVhzWGppc2owd0JuOHZkY3V6OVQteWtqTFMtTDk5ZWpGQ3dwU29NNnpBaWl1Q244?oc=5" target="_blank">DSTGA-Mamba: a disentangled spatio-temporal graph attention Mamba model for traffic flow prediction</a>  <font color="#6f6f6f">Nature</font>

Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages
Naturegeneral

Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9hcnE0ZnNkT3hja0dva0VtbXAwVjVwRUlxTVhJUHhhcWJQNTQ0bXFzUHJVeXJzRkpxdFpOTjlhaENMWFV6YjV0dm5yRHJzT2hiSWkwVEZ2RHBaek1qNjJr?oc=5" target="_blank">Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages</a>  <font color="#6f6f6f">Nature</font>

An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction
Naturegeneral

An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE54WmJfaE5ROWxRQ2htd2hVZDRySW5kWThCSHR2R0RoWUxQWTBFUWZLT0xwa1liYmFYcGZyd1BEOUgtb0YxNHN1cEhOXzVDa3RBVndXTVdqRVM3bnBidXdV?oc=5" target="_blank">An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction</a>  <font color="#6f6f6f">Nature</font>

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>

Coupled modular simplicial graph neural network with snow ablation optimization for real-time fraud detection in payment systems | Scientific Reports
Naturegeneral

Coupled modular simplicial graph neural network with snow ablation optimization for real-time fraud detection in payment systems | Scientific Reports

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE9tSzR1T1FHcUVfUGc0YlQxNnEyX2RJX1Y0a1JhanN3OU92ZlVPbTdMLTNtakE1Y0lyTjBMbHRrQ0xHSVFwOGsyaU1CUDZ4ZFppZGRjRXFTMTgwb1V5Nk1V?oc=5" target="_blank">Coupled modular simplicial graph neural network with snow ablation optimization for real-time fraud detection in payment systems | Scientific Reports</a>  <font color="#6f6f6f">Nature</font>

FFD-DHG: Financial Fraud Detection Based on Dynamic Heterogeneous Graph Representation Learning
Science Partner Journalsgeneral

FFD-DHG: Financial Fraud Detection Based on Dynamic Heterogeneous Graph Representation Learning

<a href="https://news.google.com/rss/articles/CBMiYkFVX3lxTE1lV2NwSm9Wc2tFTHJJR0x2Z0liLVY1UGNmSFhJR0ZiY1h2MFZvcDQ1N05Pem5CZDdhbERFN0w5UDVVQ1lzRHVob2k4ZjVnRURPMjM0dklpSDRacW1DSmZMYlBR?oc=5" target="_blank">FFD-DHG: Financial Fraud Detection Based on Dynamic Heterogeneous Graph Representation Learning</a>  <font color="#6f6f6f">Science Partner Journals</font>

Dynamic graph convolutional networks with Temporal representation learning for traffic flow prediction
Naturegeneral

Dynamic graph convolutional networks with Temporal representation learning for traffic flow prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFBJbkJBT2F6eXZValY4MmFzSWpxYS1ydW1ja3VqN2h5RmplVTVQNmlKckdOWHg1RmhvZEtfanJuRUp2TUZPQUpJT3VSU1ZoZkM1cXhiTmFQcmNyaFV0a1U0?oc=5" target="_blank">Dynamic graph convolutional networks with Temporal representation learning for traffic flow prediction</a>  <font color="#6f6f6f">Nature</font>

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>

Multi dynamic temporal representation graph convolutional network for traffic flow prediction
Naturegeneral

Multi dynamic temporal representation graph convolutional network for traffic flow prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE02NFVCNC05UkJDdGVNX20wMkdwbHlNX0NiWjljV1JmaGVMWHlEWUx4TGhwdndqR3ZoN0ZqNC1OdzVOdkQ0VWhxVkJFOTdMMkhzRXl2VjlNLVlFY1NEVkkw?oc=5" target="_blank">Multi dynamic temporal representation graph convolutional network for traffic flow prediction</a>  <font color="#6f6f6f">Nature</font>

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>

Application of deep learning based motion posture recognition in sports training
Naturetech

Application of deep learning based motion posture recognition in sports training

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE80eGJkVkJwZjNGcVdacktKSWJqNTA3UEhiVkhldXplMkQtZHhhbnQ5d09tc1lrSTd5U0JIQjZvUXFyVGUxa0JYZUN3eXRlbV9YaTdodW12Y2JqcWFNN3Jn?oc=5" target="_blank">Application of deep learning based motion posture recognition in sports training</a>  <font color="#6f6f6f">Nature</font>

TSGDiff: Rethinking Synthetic Time Series Generation from a Pure Graph Perspective
The Association for the Advancement of Artificial Intelligencegeneral

TSGDiff: Rethinking Synthetic Time Series Generation from a Pure Graph Perspective

<a href="https://news.google.com/rss/articles/CBMiZEFVX3lxTE9haE81YUhxYUk2QnFZS2RLM25JXzQyR2VTUWFxSUd1b1ZfMzdyTjktbS1KSEF0aDhCX0kyS1FmSlNHZ1FhUVZaQjZoV1RaeDNVTE1IVDZ0LW1ZeVZPZkJnUnJRMHQ?oc=5" target="_blank">TSGDiff: Rethinking Synthetic Time Series Generation from a Pure Graph Perspective</a>  <font color="#6f6f6f">The Association for the Advancement of Artificial Intelligence</font>

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