Top Tweets for #GraphNeuralNetwork
Invited talk by Gábor Erdős (@ELTE_UNI) at #BITS2026!
A transformer-based graph neural network for zero-shot prediction of protein thermodynamic properties, from disordered proteins to absolute stability values
#Bioinformatics #ProteinScience #MachineLearning #GraphNeuralNetwork
Enhanced Encrypted Traffic Analysis Leveraging Graph Neural Networks and Optimized Feature Dimensionality Reduction
✏️ In-Su Jung et al.
🔗 https://t.co/97Yt7Mz9Ey
Viewed: 4122; Cited: 11
#mdpisymmetry #graphneuralnetwork #metadata
SpaLP
Spatial Local Pooling
Index matrix (linear!)🤠
Cluster Visium HD 1.2M cells, 18k transcripts, 2 sections in 43 s🤯
vs adjacency matrix #GraphNeuralNetwork method BANKSY NicheCompass HERGAST
300-fold⏫computational efficiency
Cross-platform integration - STARmap PLUS MERFISH CosMx Xenium Visium HD Stereo-seq
3D spatial atlas MERFISH 8.4M cells, 239 sections on a single GPU in 4 min
+A local pooling-based spatial omics foundation model😎
@BingjDai bioRxiv 2026
https://t.co/w33guYOfc6
🎉 Call for Reading:
"Tourism Ecological Efficiency Assessment Based on Multi-Source Data Fusion and Graph Neural Network"
🔗 Full Text: https://t.co/Yfi66rEfqq
#efficiencyassessment #graphneuralnetwork #multisourcedatafusion #tourismecology #openaccess
#highlycited paper
📚Product Demand Prediction with #SpatialGraphNeuralNetworks
🔗https://t.co/0fBv9V9E4B
👨🔬by Jiale Li et al.
@nyuniversity
#demandprediction #GraphNeuralNetwork
networks hide in plain sight Dig a little deeper #graphneuralnetwork
2/ 🧠 GNN = Graph Neural Network AI, but built for humans, not bots. It maps real relationships, trust signals & interaction patterns — not just wallets and TX spam.
#GraphNeuralNetwork #ProofOfPersonhood #SybilResistance #Web3AI
#mdpisystems Call for reading:
Simplified and Adjustable #GraphDiffusion Neural Networks
https://t.co/J71LXwwW1F
by author Mr. Ji Cheol Kang and Prof. Nam-Wook Cho from MADUP Inc. and Seoul National University of Science and Technology
#IndustrialSystems #GraphNeuralNetwork
How an interpretable #graphneuralnetwork predict ultrafast electronic changes in quantum dots with incredible accuracy? Check out our paper in @ACSMatLett.
Great effort by Kushal. Thanks to @ArunKumarMK20 for collaboration.
@iitdelhi @PurdueUni @ANRFIndia
https://t.co/NlM2qKnuaM
Check this newly published article "#IndustrialInternetofThings #IntrusionDetection System Based on #GraphNeuralNetwork" at https://t.co/y3BIdB2U7U
Authors: Siqi Yang et al.
#mdpisymmetry
@ComSciMath_Mdpi
🎉 Welcome to Read #HighlyCited from #MDPICrystals
📑 #Grain Knowledge Graph Representation Learning: A New Paradigm for Microstructure-Property #Prediction
🧑🎓 by Chao Shu et al.
📌 https://t.co/9hkdxZndcs
#materialsgenome #polycrystalline #graphneuralnetwork
🧠 Graph Neural Network Learning on the Pediatric Structural Connectome
Exploring how GNNs can model the developing brain’s connectivity and advance pediatric neuroimaging.
🔗 https://t.co/w9o1jTsWH9
#Neuroimaging #GraphNeuralNetwork #AI #PediatricResearch
Air Traffic Complexity Evaluation with Hierarchical Graph Representation Learning: https://t.co/XoCk9iM8iI
#AirTrafficControl #ATC #AirTrafficComplexity #DeepLearning #FlightConflictNetwork #FCN #GraphNeuralNetwork #GNN
Urakawa, G., Fukuda, T., Yabuki, N. (2025). Automatic Floor Plan Generation System Using Graph Neural Networks Considering Room Type Information with Building Exterior Walls as Constraints, eCAADe 2025 #GraphNeuralNetwork #GraphReconstructionandGeneration #BuildingComponents
🔥 Read our Highly Cited Paper
📚Product Demand #Prediction with Spatial Graph Neural Networks
🔗https://t.co/0fBv9VabU9
👨🔬by Jiale Li et al.
@nyuniversity
#demandprediction #GraphNeuralNetwork
🔥 Read our Highly Cited Paper
📚Ransomware Detection Model Based on Adaptive #GraphNeuralNetwork Learning
🔗https://t.co/lzRCUhlg82
👨🔬by Jun Li et al.
🏫Beijing Information Science & Technology University
#adaptivediffusionconvolution #deeplearning
We invite you to read our most highly cited papers published in 2023–2024:
https://t.co/VnAtpl0Pga
#algorithms #deeplearning #reinforcementlearning #artificialintelligence #graphneuralnetwork
HybridGNN: A #SelfSupervised #GraphNeuralNetwork for Efficient Maximum Matching in Bipartite Graphs
✏️ Chun-Hui Pan et al.
🔗 https://t.co/OoO9UHeMaH
Viewed: 2475; Cited: 8
#mdpisymmetry
🌱☀️ New paper in @Build_Env!
We pitted a vanilla RNN against a directed #GraphNeuralNetwork on 15-min agrivoltaic greenhouse data:
Know when to go graph and when a simple sequence net is enough.
Check it at 🔗 https://t.co/m4TLnLgecP
#Agrivoltaics #DigitalTwin
#TsinghuaSIGS Associate Prof. Ren Zhengru’s team unleashes a multi-task #GraphNeuralNetwork to forecast wind speed & dynamic wind-shear for offshore wind farms—cutting costly met-masts & boosting green energy! 👉 https://t.co/oiz56dI2jW
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