#graphmachinelearning 搜索结果
@KuzuDB has straightforward integrations with Polars, NetworkX, Pandas, PyArrow and...Torch Geometric! Meaning that you can export data towards #GraphMachineLearning with one method call. If only they had a bolt driver for JavaScript (hint). kuzudb.com

RT Graph ML in 2023: The State of Affairs dlvr.it/SgGRKV #artificialintelligence #deeplearning #graphmachinelearning

RT Graph Machine Learning: An Overview dlvr.it/Sm01ws #graph #graphmachinelearning #machinelearning #datascience

RT Graph Machine Learning @ ICML 2023 #graphmachinelearning #artificialintelligence #ai #machinelearning dlvr.it/StGtSf

RT Temporal Graph Learning in 2023 dlvr.it/Sgz8fl #graphmachinelearning #thoughtsandtheory #stateoftheartdigest

The graph of primes exhibits some striking patterns and anomalies, both topologically and in its centrality measures.Can #GraphMachineLearning help here? Based on research with Soumya Jyoti Banerjee buff.ly/3FbO0WM #graphs

The Deep Graph Library (DGL) reached v1.0 and is packed with new features, like hypergraph neural nets, CUDA streams, hetero graph explainers and more. buff.ly/3Y4nFRi #GraphMachineLearning

GraphScope (by Alibaba) is a unified distributed graph computing platform that provides a one-stop environment for performing diverse graph operations on a cluster through a user-friendly Python interface buff.ly/3LG76Yp #GraphMachineLearning #Graphs

Thanks to #DrPlabanBhowmick for his excellent theory session on the 'Introduction to #GraphMachineLearning' on the eve of the 5-Day Mid Career Training Program (#MCTP) on the Foundation Course on #AI and #BigData for #ISS officers at #IITKharagpur on November 13. @plabanb

You can now use PyTorch Geometric (PyG) on Graphcore IPUs to accelerate #GraphMachineLearning. buff.ly/3zSxVCc @PyG_Team

Kùzu as a Pytorch Geometric (PyG) Remote Backend: you can now train PyG GNNs and other models directly using graphs (and node features) stored inside @kuzudb . buff.ly/3GGt8Yp #GraphMachineLearning #GraphDatabase

Using #GraphMachineLearning when your data is not a #graph? K-nearest neighbor graphs are not a good solution in fully supervised #machinelearning scenarios. Learn why in the #NeurIPS23 paper by @federico_errica. Read here: neclab.eu/research-areas…. #NECLabs

🔥 Read our Highly Cited Paper 📚Prediction of Water Leakage in Pipeline Networks Using Graph Convolutional Network Method 🔗mdpi.com/2076-3417/13/1… 👨🔬 by Dr. Ersin Şahin et al. #graphconvolutionalnetwork #graphmachinelearning

Peng Fang presenting our work ''Distributed Graph Embedding with Information-Oriented Random Walks'' @ #VLDB2023 #VLDB23. There will also be a poster session in the afternoon #GraphMachineLearning #DistributedGraphSystems Paper vldb.org/pvldb/vol16/p1… Blog big-graph-live.blogspot.com/2023/07/distri…

How to Improve Graph Machine Learning Performance! tinyurl.com/5n6w5uc7 #GraphMachineLearning #MachineLearning #Graph #OptimizingGraphMachineLearningModels #StrategiesToBoostGMLPerformance #AI #AINews #AnalyticsInsight #AnalyticsInsightMagazine

Gemini Flash 2.0 really digs deep! Good thing it caught the flaws before reviewers did. Time to tighten those proofs! #GraphMachineLearning
The latest @Neo4j Graph Data Science v2.3 library has (finally) heterogeneous embeddings and an improved Python GDS library. #GraphMachineLearning buff.ly/3YAi1H5 buff.ly/3HOlHz8

📢 New article alert! Explore the pioneering framework TEA-GLM, leveraging large language models for zero-shot graph machine learning. Uncover how it enhances effectiveness in zero-shot scenarios. Read more here: bit.ly/4dCc04z #graphmachinelearning #LLMs #TEAGLM
Gemini Flash 2.0 really digs deep! Good thing it caught the flaws before reviewers did. Time to tighten those proofs! #GraphMachineLearning
Thanks to #DrPlabanBhowmick for his excellent theory session on the 'Introduction to #GraphMachineLearning' on the eve of the 5-Day Mid Career Training Program (#MCTP) on the Foundation Course on #AI and #BigData for #ISS officers at #IITKharagpur on November 13. @plabanb

Understanding #GraphMachineLearning in the Era of Large Language Models (#LLMs) isamu-website.medium.com/understanding-…
🔥 Read our Highly Cited Paper 📚Prediction of Water Leakage in Pipeline Networks Using Graph Convolutional Network Method 🔗mdpi.com/2076-3417/13/1… 👨🔬 by Dr. Ersin Şahin et al. #graphconvolutionalnetwork #graphmachinelearning

A preprint of our workshop report ''LLM+KG: Data Management Opportunities in Unifying Large Language Models+Knowledge Graphs'' is available here: arxiv.org/pdf/2410.01978 #LLMs #KnowledgeGraphs #GraphMachineLearning #GraphDataManagement #GraphRAG #VLDB24 #VLDB2024
🌟Excited for the "LLM+KG: Data Management Opportunities in Unifying Large Language Models + Knowledge Graphs" workshop at #VLDB2024! 🚀 #AI #NLP #KnowledgeGraphs #DataScience #LLM This session will begin at 9:00 AM on August 26th! For more details: seucoin.github.io/workshop/llmkg/

📢 New article alert! Explore the pioneering framework TEA-GLM, leveraging large language models for zero-shot graph machine learning. Uncover how it enhances effectiveness in zero-shot scenarios. Read more here: bit.ly/4dCc04z #graphmachinelearning #LLMs #TEAGLM
🕵️♀️ Explore #GraphMachineLearning for fraud detection with Node Classification! Dive into the world of #GraphML and see how it can help detect fraudulent activities. @Yelp #MachineLearning #memgraph #memgraphdb #graphdatabase #database memgraph.com/blog/4-reasons…
memgraph.com
4 Reasons Why Graph Tech Is Great for Knowledge Graphs
Use graph databases to unify dispersed data, enhance real-time analysis, and scale efficiently with dynamic algorithms.
Blog post (big-graph-live.blogspot.com/2024/05/view-b…) for our paper "View-based Explanations for Graph Neural Networks" - T. Chen, D. Qiu, Y. Wu, A. Khan, X. Ke, and Y. Gao, to be presented @SIGMODConf #SIGMOD2024 #SIGMOD24 #GraphMachineLearning #GraphDataManagement #DatabaseViews #ExplainableAI
Find the preprint arxiv.org/abs/2401.02086 of our paper ''View-based Explanations for Graph Neural Networks'' accepted at @SIGMODConf #SIGMOD2024 #SIGMOD24 #GraphMachineLearning #GraphDataManagement #DatabaseViews #ExplainableA
Blog post (big-graph-live.blogspot.com/2024/05/genera…) for our #ICDE2024 #ICDE24 IEEE ICDE Conference paper on "Generating Robust Counterfactual Witnesses for Graph Neural Networks" - D. Qiu, M. Wang, A. Khan, and Y. Wu #GraphMachineLearning #GraphDataManagement #ExplainableAI.
stay tuned for the camera-ready of our #ICDE2024 #ICDE24 IEEE ICDE Conference paper on "Generating Robust Counterfactual Witnesses for Graph Neural Networks" 👇 #GraphMachineLearning #GraphDataManagement #ExplainableAI.
How to Improve Graph Machine Learning Performance! tinyurl.com/5n6w5uc7 #GraphMachineLearning #MachineLearning #Graph #OptimizingGraphMachineLearningModels #StrategiesToBoostGMLPerformance #AI #AINews #AnalyticsInsight #AnalyticsInsightMagazine

🕵️♀️ Explore #GraphMachineLearning for fraud detection with Node Classification! Dive into the world of #GraphML and see how it can help detect fraudulent activities. @Yelp #MachineLearning #memgraph #memgraphdb #graphdatabase #database memgraph.com/blog/4-reasons…
memgraph.com
4 Reasons Why Graph Tech Is Great for Knowledge Graphs
Use graph databases to unify dispersed data, enhance real-time analysis, and scale efficiently with dynamic algorithms.
🕵️♀️ Explore #GraphMachineLearning for fraud detection with Node Classification! Dive into the world of #GraphML and see how it can help detect fraudulent activities. @Yelp #MachineLearning #memgraph #memgraphdb #graphdatabase #database memgraph.com/blog/4-reasons…
memgraph.com
4 Reasons Why Graph Tech Is Great for Knowledge Graphs
Use graph databases to unify dispersed data, enhance real-time analysis, and scale efficiently with dynamic algorithms.
Thanks to #DrPlabanBhowmick for his excellent theory session on the 'Introduction to #GraphMachineLearning' on the eve of the 5-Day Mid Career Training Program (#MCTP) on the Foundation Course on #AI and #BigData for #ISS officers at #IITKharagpur on November 13. @plabanb

RT Graph Machine Learning @ ICML 2023 #graphmachinelearning #artificialintelligence #ai #machinelearning dlvr.it/StGtSf

RT Temporal Graph Learning in 2023 dlvr.it/Sgz8fl #graphmachinelearning #thoughtsandtheory #stateoftheartdigest

RT Graph Machine Learning: An Overview dlvr.it/Sm01ws #graph #graphmachinelearning #machinelearning #datascience

RT Graph ML in 2022: Where Are We Now? dlvr.it/SGFGJV #graphmachinelearning #knowledgegraph #deeplearning

RT Graph ML in 2023: The State of Affairs dlvr.it/SgGRKV #artificialintelligence #deeplearning #graphmachinelearning

RT Machine Learning on Graphs, Part 3 dlvr.it/S8lLdv #graphmachinelearning #scalablemachinelearning #graphkernels

RT Machine learning on graphs, Part 2. dlvr.it/S84PJm #embedding #randomwalk #graphmachinelearning #machinelearning

RT Skip-Gram Neural Network for Graphs dlvr.it/S4H9qZ #graphmachinelearning #nlp #machinelearning #skipgram #ai

RT GraphGPS: Navigating Graph Transformers dlvr.it/SSBHTy #graphmachinelearning #artificialintelligence #computerscience

How to Improve Graph Machine Learning Performance! tinyurl.com/5n6w5uc7 #GraphMachineLearning #MachineLearning #Graph #OptimizingGraphMachineLearningModels #StrategiesToBoostGMLPerformance #AI #AINews #AnalyticsInsight #AnalyticsInsightMagazine

Using #GraphMachineLearning when your data is not a #graph? K-nearest neighbor graphs are not a good solution in fully supervised #machinelearning scenarios. Learn why in the #NeurIPS23 paper by @federico_errica. Read here: neclab.eu/research-areas…. #NECLabs

🔥 Read our Highly Cited Paper 📚Prediction of Water Leakage in Pipeline Networks Using Graph Convolutional Network Method 🔗mdpi.com/2076-3417/13/1… 👨🔬 by Dr. Ersin Şahin et al. #graphconvolutionalnetwork #graphmachinelearning

Excited to announce our next talk (and the first of 2022!): Speaker: @PeterWBattaglia Date/Time: Jan 13, 3:00pm CET Title: Modeling physical structure and dynamics using graph-based machine learning #graphmachinelearning Follow us and register at dsiseminar.github.io!

Open source #graphmachinelearning library StellarGraph has launched a series of #algorithms for network graph analysis to discover patterns in #data, work with larger data sets and speed up performance while reducing memory usage. Access the library here: bit.ly/2L6n7Xy
How to design end-to-end visual solutions for graph machine learning while ensuring a user-friendly experience - a Data61 UX Designer on making data accessible, purposeful, and tangible: bit.ly/2VHKNrX #graphmachinelearning #machinelearning #userexperience
Peng Fang presenting our work ''Distributed Graph Embedding with Information-Oriented Random Walks'' @ #VLDB2023 #VLDB23. There will also be a poster session in the afternoon #GraphMachineLearning #DistributedGraphSystems Paper vldb.org/pvldb/vol16/p1… Blog big-graph-live.blogspot.com/2023/07/distri…

@KuzuDB has straightforward integrations with Polars, NetworkX, Pandas, PyArrow and...Torch Geometric! Meaning that you can export data towards #GraphMachineLearning with one method call. If only they had a bolt driver for JavaScript (hint). kuzudb.com

Something went wrong.
Something went wrong.
United States Trends
- 1. Flacco 86K posts
- 2. Bengals 81.1K posts
- 3. Bengals 81.1K posts
- 4. Tomlin 21.9K posts
- 5. #clubironmouse 3,024 posts
- 6. Ramsey 19.2K posts
- 7. #criticalrolespoilers 8,074 posts
- 8. Chase 107K posts
- 9. Chase 107K posts
- 10. #WhoDidTheBody 1,608 posts
- 11. #TNFonPrime 5,619 posts
- 12. #WhoDey 6,887 posts
- 13. yeonjun 117K posts
- 14. Cuomo 84.7K posts
- 15. Teryl Austin 2,816 posts
- 16. Andrew Berry 3,279 posts
- 17. Xenoverse 3 N/A
- 18. Tame Impala 5,565 posts
- 19. Max Scherzer 14.5K posts
- 20. Burrow 9,908 posts