🧠➡️🤖 This paper shows how oscillatory sync can power “HoloGraph” a brain-inspired model outperforming classic #GNNs on complex structures

www.nature.com/articles/s41... #AI

Bayesian Neighborhood Adaptation for Graph Neural Networks

Paribesh Regmi, Rui Li, Kishan K C

Action editor: Peilin Zhao

https://openreview.net/forum?id=2zEemRib3a

#gnns #gnn #node

#urbananalytics #graphanalysis #opensource #datascience #geospatial #networkscience #urbanplanning #python #spatialanalysis | Yuta Sato | 34 comments 🚀 𝗰𝗶𝘁𝘆𝟮𝗴𝗿𝗮𝗽𝗵 𝘃𝟬.𝟭.𝟲 𝗶𝘀 𝗻𝗼𝘄 𝗹𝗶𝘃𝗲! 🚀 city2graph is a Python library that converts geospatial datasets into graphs (networks). 🔗 GitHub https://lnkd.in/gmu6bsKR What's New: 🛣️ 𝐌𝐞𝐭𝐚𝐩𝐚𝐭𝐡𝐬 𝐟𝐨𝐫 𝐇𝐞𝐭𝐞𝐫𝐨𝐠𝐞𝐧𝐞...

[Repo:] Get Mapping & Graphing with city2graph

Great news for graph + geospatial folks out there: city2graph is a #Python library that transforms #geospatial / #GIS datasets into graph representations for spatial network analysis and graph neural networks ( #GNNs).

Repo: github.com/c2g-dev/city...

Exploring and Improving Initialization for Deep Graph Neural Networks: A Signal Propagation Persp...

Senmiao Wang, Yupeng Chen, Yushun Zhang, Ruoyu Sun, Tian Ding

Action editor: Kenta Oono

https://openreview.net/forum?id=6Aj0aNXfRy

#deepen #gcns #gnns

Evaluating explainability techniques on discrete-time graph neural networks

Manuel Dileo, Matteo Zignani, Sabrina Tiziana Gaito

Action editor: Christopher Morris

https://openreview.net/forum?id=JzmXo0rfry

#explainability #temporal #gnns

And before I forget, I still have 1 more PhD position available @csaudk.bsky.social to be filled by November 2025. We will work on bleeding-edge topics in #NLProc #LLMs #AIAgents #GNNs (e.g., Graph Foundation Models, knowledge-seeking agents, and more).

🧵6/6

0) What are Graphs?

Kicking off our #GNNs tutorial!

First, the core: a graph is a mathematical structure modeling relationships.

For GNNs, these are the fundamental data: nodes (entities) & edges (their connections).

💥It's tutorial time for #GraphNeuralNetworks!

Here's a first step-by-step towards understanding how GNNs work.

Sometimes, a refresh is exactly what you need. #GNNs #AI

🧵

KAGNNs: Kolmogorov-Arnold Networks meet Graph Learning

Roman Bresson, Giannis Nikolentzos, George Panagopoulos et al.

Action editor: Chuxu Zhang

https://openreview.net/forum?id=03UB1MCAMr

#graph #gnns #node

PROXI: Challenging the GNNs for Link Prediction

Astrit Tola, Jack Myrick, Baris Coskunuzer

Action editor: Petar Veličković

https://openreview.net/forum?id=u9EHndbiVw

#nodes #gnn #gnns

🔥Our paper "BioX-CPath: Biologically-driven explainable Diagnostics for Multistain IHC omputational Pathology" was accepted at #CVPR2025!

🚀We'll be releasing the paper and code repo ASAP, stay tuned! #multistain #IHC #pathology #ExplainableAI #GNNs #PrecisionMedicine #Immunolog

A new customer for Septentrio! -> BRASAL MARINE SERVICES (CY) LTD has chosen the GNSS AsteRx-U3 + HYPACK for precise positioning of blocks in maritime construction. A happy customer indeed!
#GNNS #Maritime #Construction #dredging #crane #Limassol
www.nautilusoceanica.com/categoria-pr...

Re-reading these wonderful pieces preparing for what comes in 2025 😉
#GNNs #deeplearning #genomics #bioinformatics

Advanced atom-level representations for protein flexibility prediction utilizing graph neural networks Protein dynamics play a crucial role in many biological processes and drug interactions. However, measuring, and simulating protein dynamics is challenging and time-consuming. While machine learning h...

Last year, I collaborated with Congruence Therapeutics by developing a framework using graph neural nets (GNNs) to predict protein flexibility (via the B-factor) at the atomic level. We shared a preprint of the first iteration of this work: arxiv.org/abs/2408.12519. A thread. #GNNs #drugdiscovery

🚀 Don’t miss our #LoG2024 poster on Tue, Nov 28 @ 15:00 GMT!

Join us to discuss GNNs + LLMs for disinformation detection. The conference registration is free!
#FakeNewsDetection #GNNs #AI #LLMs @logconference.bsky.social

New Paper: Knowledge Graph Based Recommender for Automatic Playlist Continuation Our latest research has just been published in the MDPI Information Journal. The paper, titled "Knowledge Graph Based Recommender for Automatic Playlist Continuation" explores and demonstrates the...

You can also check out our blogpost for the paper: blog.mjovanovik.com/post/7507363...

#KnowledgeGraphs #GNN #GNNs #RecommenderSystems #OpenAccess #Academia #Blog

Knowledge Graph Based Recommender for Automatic Playlist Continuation In this work, we present a state-of-the-art solution for automatic playlist continuation through a knowledge graph-based recommender system. By integrating representational learning with graph neural ...

If you're interested in GNNs and recommender systems based on Knowledge Graphs, take a look at our paper published last year, "Knowledge Graph Based Recommender for Automatic Playlist Continuation".

www.mdpi.com/2078-2489/14...

#KnowledgeGraphs #GNN #GNNs #RecommenderSystems #OpenAccess #Academia

SparkFun RTK Torch is a compact and waterproof GNSS surveyor with RTK functionality - CNX Software SparkFun’s RTK Torch is a real-time kinematic (RTK) surveying device that offers tri-band reception, tilt compensation, and millimeter accuracy in a

.@SparkFun RTK Torch is a portable waterproof #GNNS surveyor using RTK technology for millimeter accuracy, #ESP32 for WiFi and Bluetooth connectivity, and STM32WL LoRa SoC. #SmartAgriculture #GPS #landsurveying #STM32

cnx-software.com/2024/05/06/spa…

u-blox unveils miniature MIA-M10 GPS module - CNX Software u-blox has introduced what could be the world's smallest GNSS module with the 4.5x4.5mm u-blox MIA-M10 miniature module supporting GPS, BeiDou, Galileo,

.@ublox has launched what could be the world's smallest #GNNS module with the 4.5x4.5mm MIA-M10 module. #gps #semiconductors #electronics

cnx-software.com/2022/06/17/u-b…

Performance-Adaptive Sampling Strategy (PASS) for GNNs: O...

Performance-Adaptive Sampling Strategy (PASS) for #GNNs: Open sourcing PASS engineering.linkedin.com/blog/2022/open-sourcing-... #MachineLearning #DeepLearning #ML