#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

TheOrbifold's tweet image. @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

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

TheOrbifold's tweet image. 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

TheOrbifold's tweet image. 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

TheOrbifold's tweet image. 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

sabyasachi_uni's tweet image. 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

TheOrbifold's tweet image. 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

TheOrbifold's tweet image. 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

NECLabsEU's tweet image. 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

Applsci's tweet image. 🔥 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…

rijitK's tweet image. 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…

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

TheOrbifold's tweet image. 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

sabyasachi_uni's tweet image. 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

🔥 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

Applsci's tweet image. 🔥 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/

VLDB2024's tweet image. 🌟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


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.



未找到 "#graphmachinelearning" 的结果

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

sabyasachi_uni's tweet image. 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

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

NECLabsEU's tweet image. 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

Applsci's tweet image. 🔥 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!

DegasSeminar's tweet image. 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…

rijitK's tweet image. 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

TheOrbifold's tweet image. @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

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