#graphml zoekresultaten
🏆 CIKM 2025 Best Full Paper Award! 🚀 We are thrilled to announce that we have won the prestigious Best Full Paper Award at CIKM 2025 for our work, "Reconsidering the Performance of GAE in Link Prediction"! 🎉 #CIKM2025 #GraphML #BestPaper
Always happy to chat about graphs, generative models, or spatial omics while in San Diego. 🌊 See you there! 1️⃣openreview.net/forum?id=d2Eou… 2️⃣openreview.net/forum?id=5ofJy… 3️⃣ arxiv.org/abs/2509.06743 #MachineLearning #GraphML #GenerativeModels #SpatialTranscriptomics
With Legendary prof. Xavier Bresson #graph #graphml #machinelearning #ml #AI #ArtificialIntelligence #mathematics
“DiffGR: A Discrete Diffusion‑Based Model for Personalised Recommendation by Reconstructing User‑Item Bipartite Graphs” Meet DiffGR here 👇 link.springer.com/chapter/10.100… #GraphML #Recommendation #DiffusionModels
Ecstatic✨ to share that I'm headed to @CarnegieMellon @mldcmu for a Ph.D. in Machine Learning this Fall! As I gear up to graduate from @IIITDelhi👨🏻🎓 with a #BTech in #csai, I'm exhilarated for this exciting new journey at @SCSatCMU. I'll be working on #GraphML & #NLProc!
Finally leveraging the opportunity to attend events in Bay Area. Very excited! @Stanford #GraphML #workshop
Meet Quantum-Evolution-Kernel, Pasqal’s first open-source tool for applying quantum computing to graph machine learning—no quantum computer needed! Try it out and join us in shaping the future of quantum computing: github.com/pasqal-io/quan… #OpenSource #GraphML #QuantumML
From Graph Benchmark Challenges to future #GNN breakthroughs, this #GraphML piece from @Mila_Quebec's @michael_galkin is a must-read for anyone working with Graph Neural Networks in 2023 ⬇️ hubs.la/Q01wRfd10
The @LogConference, the leading conference dedicated to graph machine learning, is happening! Submission deadline: September 11th, 2024 Final decision: November 13th, 2024 Don't miss out on this opportunity! More details at logconference.org/cfp/#LoG2024 #GraphML #MachineLearning…
My latest article: “Unleashing the Power of Data: Integrating Knowledge Graphs and Retrieval Augmented Generation with…” by Jason Kronemeyer #GraphDataScience #GraphML #Neo4j #JKnowledge medium.com/@jfkrone/unlea…
The preprint of our work "DINE: Dimensional Interpretability of Node Embeddings", made with @meghakhosla, @apanisson and @run4avi is out on @arxiv! Great collaboration that started with a @SoBigData Transnational Access. arxiv.org/abs/2310.01162 #TNA #XAI #GraphML
Excited to share that I’ve joined @Meta as a Visiting Researcher for the next year, in their Pittsburgh office, alongside my PhD at @mldcmu. I’ll be working on #GeometricDL and #GraphML, with @YinglongXia & @zimplex4, under the @AIatMeta AI Mentorship Program.
📢 I am going on the job market for 2024! I've built pipelines with stats & ML methods (including #GraphML) applied to -omics datasets for biomarker discovery. I'm looking for industry & academia positions. Pls reach out if you're hiring or you've advice for the job search! 🤗
🛠️ Want to simplify your data analysis? Dr. Ashleigh N. Faith breaks down how Tom Sawyer Software's suite empowers you to use graphML effortlessly. No coding? No problem! Watch her insightful review and unlock your data's potential: hubs.li/Q03dBwQ80 #GraphML #TechReview…
𝗚𝗿𝗮𝗽𝗵𝘀 + 𝗟𝗟𝗠𝘀: 𝗔 𝗡𝗮𝘁𝘂𝗿𝗮𝗹 𝗙𝗶𝘁? Glad to share our latest preprint: Graph Linearization Methods for Reasoning on Graphs with Large Language Models (now on arXiv: arxiv.org/abs/2410.19494) #LLMs #GraphML #NLP #AIResearch #MultimodalAI
🚨 Exciting news! We released 🎱 tgp (Torch Geometric Pool), the library for pooling in Graph Neural Networks. 🚀 Get started with our tutorials: torch-geometric-pool.readthedocs.io/en/latest/tuto… With @IvanMarisca and Carlo Abate. #GraphML #GNN #Pooling #Pyg
Always happy to chat about graphs, generative models, or spatial omics while in San Diego. 🌊 See you there! 1️⃣openreview.net/forum?id=d2Eou… 2️⃣openreview.net/forum?id=5ofJy… 3️⃣ arxiv.org/abs/2509.06743 #MachineLearning #GraphML #GenerativeModels #SpatialTranscriptomics
🙏 A big thank you to the reviewers, thoughtful reviews, constructive points, & even disagreements. We truly appreciate the time, and efforts. 💻 🧵 📄 Code & Data, X thread, Preprint in thread. github.com/rethinking-gra… #GraphML #LanguageModels #MultimodalAI #GraphReasoning
“DiffGR: A Discrete Diffusion‑Based Model for Personalised Recommendation by Reconstructing User‑Item Bipartite Graphs” Meet DiffGR here 👇 link.springer.com/chapter/10.100… #GraphML #Recommendation #DiffusionModels
🏆 CIKM 2025 Best Full Paper Award! 🚀 We are thrilled to announce that we have won the prestigious Best Full Paper Award at CIKM 2025 for our work, "Reconsidering the Performance of GAE in Link Prediction"! 🎉 #CIKM2025 #GraphML #BestPaper
(7/7) More at 👇 📘 FedGraph: openreview.net/forum?id=d48Hj… 📘 FedLink: openreview.net/forum?id=D7PiC… 🌍 Federated Graph Learning — shaping the next frontier of privacy-aware, multi-agent AI. #NeurIPS2025 #GraphML #FederatedLearning #PrivacyAI #FedGraph #FedLink #AIResearch
This article tests how degree, clustering, and topology–feature ties sway GNN and feature-only models using HypNF synthetic graphs. - hackernoon.com/choose-the-rig… #graphml #gnnbenchmark
Synthetic HypNF graphs reveal GNN fragilities: HGCN beats GCN on dense, homogeneous nets but falters on sparse power-law ones. - hackernoon.com/a-hyperbolic-b… #graphml #gnnbenchmark
🚀 New move spotted: @karishgrover joins Meta AI as a Visiting Researcher, while pursuing his PhD at CMU. His work? #GeometricDL & #GraphML 🌐 Check out his profile on @dinq_io ⬇️
Excited to share that I’ve joined @Meta as a Visiting Researcher for the next year, in their Pittsburgh office, alongside my PhD at @mldcmu. I’ll be working on #GeometricDL and #GraphML, with @YinglongXia & @zimplex4, under the @AIatMeta AI Mentorship Program.
Excited to share that I’ve joined @Meta as a Visiting Researcher for the next year, in their Pittsburgh office, alongside my PhD at @mldcmu. I’ll be working on #GeometricDL and #GraphML, with @YinglongXia & @zimplex4, under the @AIatMeta AI Mentorship Program.
Have you checked out S-CGIB? github.com/NSLab-CUK/S-CG… Our molecular graph model, accepted at #AAAI25, showed #SOTA results on molecular property prediction. A gentle reminder to explore! 🚀 #GraphML #GNNs #SOTA
A quick reminder: Workshop on Graph-Augmented LLMs (GaLM) at @ICDM2025 is still accepting submissions! #LLM #GraphML #GraphAnalytics 📝 Papers — Extended deadline: September 5 More Info to submit your work here: iitbhu.ac.in/cf/jcsic/activ…
With Legendary prof. Xavier Bresson #graph #graphml #machinelearning #ml #AI #ArtificialIntelligence #mathematics
🧬 Thu 7 Aug | 5 PM EAT: Dr Michalis K. Titsias (DeepMind) on Learning-Order Autoregressive Models for Molecular Graph Gen 🚀 SOTA on QM9 & ZINC250k! 🔗 calendar.app.google/X2JaaTwLsaVSqV… 🌐 theciggroup.net #AI #GraphML #DeepMind #CIG
Promotional Video: youtube.com/watch?v=hEeCuv… #GraphML #ResponsibleAI 👇
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KDD 2025 - Finding Counterfactual Evidences for Node Classification
Come to the paper & poster sessions of my PhD student @DazhuoQiu @kdd_news #KDD25 #KDD2025 for our paper "𝘍𝘪𝘯𝘥𝘪𝘯𝘨 𝘊𝘰𝘶𝘯𝘵𝘦𝘳𝘧𝘢𝘤𝘵𝘶𝘢𝘭 𝘌𝘷𝘪𝘥𝘦𝘯𝘤𝘦𝘴 𝘧𝘰𝘳 𝘕𝘰𝘥𝘦 𝘊𝘭𝘢𝘴𝘴𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯" arxiv.org/pdf/2505.11396 (work w/ @FrancescoBonchi) 👇
What if message passing in GNNs followed hyperbolic PDEs? This work reformulates GNN dynamics as a hyperbolic PDE system, mapping node features into eigenvector solution spaces unlocking topological interpretability Boosts performance across graph tasks #GraphML #icml2025 #AI #ML
🚨 Reviewer Call — LoG 2025 📷 Passionate about graph ML or GNNs? Help shape the future of learning on graphs by reviewing for the LoG 2025 conference! 📷forms.gle/Ms21k7oE8kF1Pd… 📷 RT & share! #GraphML #GNN #ML #AI #CallForReviewers
Just read a cool paper at #ICML2025: ML2-GCL – a manifold learning inspired, lightweight GCL method that: 1. Avoids risky augmentations with single-view design 2. Recovers global structure from local fits 3. Offers a closed-form solution, boosting efficiency #GraphML #AI #ML #DL
🚨 Calling all ML & AI companies! The LOG 2025 sponsor page is now live: logconference.org/sponsors/ LOG is the go-to venue for graph ML, reasoning & systems research. We're inviting sponsors to support this fast-growing community & gain visibility. #LOG2025 #GraphML #MachineLearning
Excited to be in Vancouver this week for #ICML2025!🌍✈️. Presenting our paper on curvature-based graph anomaly detection: 📍 East Exhibition Hall A-B E2900 📅 Tue, 15 July | 4:30 – 7:00 PM PDT 🔗 arxiv.org/abs/2502.08605 Drop by to chat about #geometricDL and #graphML! 🚀🧩
New paper alert! 🚀📈 #ICML2025 @icmlconf Can graph curvature uncover hidden anomalies overlooked by traditional methods? 💡Introducing CurvGAD, a mixed-curvature graph autoencoder designed to detect curvature-based geometric anomalies. 🔗 arxiv.org/pdf/2502.08605 (1/9)
🏆 CIKM 2025 Best Full Paper Award! 🚀 We are thrilled to announce that we have won the prestigious Best Full Paper Award at CIKM 2025 for our work, "Reconsidering the Performance of GAE in Link Prediction"! 🎉 #CIKM2025 #GraphML #BestPaper
💥 Graph Algorithms for Data Science by @tb_tomaz. okt.to/kpMI2a @manningbooks #graphML #neo4j #Cypher #graphdb #graphanalytics #datascience #NLP #twin4j
New GNNs? On Tuesday in the #GraphML reading group James Rowbottom and @b_p_chamberlain present their "GRAND: Graph Neural Diffusion" + their #NeurIPS2021 paper "Beltrami Flow and Neural Diffusion on Graphs" out of @mmbronstein's group @Twitter! Zoom: hannes-stark.com/logag-reading-… 1/2
I just wrote a blog for all of you who want to step into this beautiful world of Graph ML but you're not sure how to start. Blog: gordicaleksa.medium.com/how-to-get-sta… I shared exciting applications. I shared and structured the resources. And much more. #graphml
KeyError exception while reading a GraphML file with NetworkX occurs in Visual Studio 2017 but not Spyder stackoverflow.com/questions/6537… #visualstudio2017 #python #graphml #networkx
Day 12 of #100DaysOfCode Revisited spectral clustering lecture. Oh, the magic of eigendecomposition 🧙♀️✨ #GraphML #AI #WomenWhoCode #WomenInSTEM
Days 68 & 69 of #100Daysofcode ✅ Created my own dataset from PyG's InMemoryDataset class (see below MyOmicsDataset) ➡️ Stored 578 graphs on it ➡️ Each graph having nodes features & graph label #GraphML #WomenWhoCode #WomenInSTEM
Day 71-76 of #100DaysOfCode For a graph-level classification task: ✅Trained a GCN-based model ✅Trained a Chebnet-based model #GraphML #geometricDL #WomenInSTEM #WomenWhoCode
How to create Heterogeneous GNNs using PyTorchGeometric. ⭐️ Using to_hetero(): Convert a homogeneous GNN model to a heterogeneous GNN. ⭐️ Using HeteroConv: This allows you to define custom heterogeneous message-passing functions for different edge types. #gnn #nn #graphml #pyg
Days 5 & 6 of #100DaysOfCode ✅ Finished Homework 1 of the #CS224W course ✅ Uploaded to github Next week I'll deepen into feature-based methods and community detection algorithms. #GraphML #AI #WomenWhoCode #womenintech
Ecstatic✨ to share that I'm headed to @CarnegieMellon @mldcmu for a Ph.D. in Machine Learning this Fall! As I gear up to graduate from @IIITDelhi👨🏻🎓 with a #BTech in #csai, I'm exhilarated for this exciting new journey at @SCSatCMU. I'll be working on #GraphML & #NLProc!
Day 9 of #100daysofcodechallenge Today I learned the notion of encoders/decoders applied to nodes in a graph. Deepwalk and node2vec methods coming in the next day(s). #GraphML #AI #WomenWhoCode #WomenInSTEM #100DaysOfCode
Day 10 of #100DaysOfCode Today I covered random walk approaches for node embeddings: deepwalk & node2vec. The conclusion of this lecture and last one(s) is... 👇 #GraphML #WomenWhoCode #AI
Day 23 & 24 #100DaysOfCode Holidays are over and I've been working on classical #GNN layers: how they r defined, which components they include. Some architectrs: GCN, GraphSAGE & GAT. Combine different aspects of design ➡️ performance🆙 #GraphML #AI #WomenWhoCode #womenintech
After a hectic month off the #100DaysOfCode challenge, I'm back. Day 52!💥🦾 👉Working on @m_deff 's GCNN implementation for a signal classification task in #Keras ✅Loaded + numpyed features, adj matrix & labels 🚧Coarsening the graph #GraphML #AI #WomenWhoCode #WomenInSTEM
🚀 Unlock the future of data science with our comprehensive suite featuring Graph Analytics, GraphML, and Graph-Powered GenAI, powered by the ArangoDB LangChain Integration Pack! Register Now:- okt.to/Sm5g7P #DataScience #GraphML #GraphRAG #LangChain
Day 31 of #100DaysOfCode Inference with Belief propagation on Conditional Random Field (a special case of Markov Random Fields to model conditional prob. distribution) I was a bit rusty on cond. probs but I went thru in the end!🙌 #GraphML #AI #WomenWhoCode #womenintech
Finally leveraging the opportunity to attend events in Bay Area. Very excited! @Stanford #GraphML #workshop
New year is a good time to is a good time to recap and make predictions. In a new post in @TDataScience I sought the opinion of 12 prominent researchers in the field of #GraphML to predict what is in store for 2021. towardsdatascience.com/predictions-an…
Day 60 of #100DaysOfCode I've been playing with Cora dataset: Node degree distribution, found the most connected nodes in the network, explored the classes and the notion of homophily. And then the best part 👇 #GraphML #WomenWhoCode #WomenInSTEM
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