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Articles

Neo4j ETL using Airflow

January 16, 2023/by Orbifold

Memgraph

November 29, 2022/by Orbifold

NetworkX: an overview

November 21, 2022/by Orbifold
DRKG Visualization

Drug Repurposing using TigerGraph and Graph Machine Learning

February 12, 2022/by Orbifold
Syncfusion

Syncfusion diagramming

December 14, 2021/by Orbifold

Entity resolution can be easy

November 5, 2021/by Orbifold

Graph Machine Learning using TensorFlow

February 2, 2020/by Orbifold

Using GraphSage for node predictions

November 3, 2019/by Orbifold

Graph Link Prediction using GraphSAGE

November 1, 2019/by Orbifold

Using Laplacians for graph learning

October 30, 2019/by Orbifold

Community detection using NetworkX

October 7, 2019/by Orbifold

What is a graph database?

October 1, 2019/by Orbifold

Graph attention networks

September 29, 2019/by Orbifold
Cora data set

The Cora dataset

September 29, 2019/by Orbifold

Node2Vec with weighted random walks

September 26, 2019/by Orbifold

Node2Vec embedding

September 26, 2019/by Orbifold
Spark GraphFrame

Spark GraphFrame Basics

August 16, 2019/by Orbifold
Towards persistent homology

What is persistent homology?

November 2, 2018/by Orbifold

Apache Jena disaster

October 31, 2018/by Orbifold
Vaticle TypeDB

TypeDB by Vaticle

October 31, 2018/by Orbifold
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Orbifold B.V.
Leuven, Belgium (Europe)
info@orbifold.net
orbifold.net

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16 hours ago
Visualize big networks within seconds with Cosmograph. Halfway art and science, uses your GPU to speed up force-directed layout. With timeline and graph analytic filtering. And yes, open source. https://t.co/NfTrbKSsgj #Graphs #DataViz https://t.co/Y2jdU6Zx9S
14 days ago
Codon by @exaloop , a high-performance Python compiler that compiles to native machine code without any runtime overhead. Speedups are on the order of 10-100xor more, on a single thread. Codon's performance is typically on par with that of C/C++. https://t.co/g00nZsyR64 #python https://t.co/KbeSpO8IYw
16 days ago
Trillion edges benchmark: new world record beyond 100TB by @TigerGraphDB featuring AMD based Amazon EC2 instances. https://t.co/65sp9zkwPY #GraphDatabase https://t.co/d9BVCsOzem
18 days ago
Watch this space for an updated PowerBI widget based on @yworks. In 5 years since v1 it's easier to create and more powerful (Power Apps, Python & R integration...). Developing graph visualization in @MSPowerBI is so much easier and more fun than Tableau. https://t.co/XOQvZc9FbH https://t.co/iQ0I6n7EOi
18 days ago
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 https://t.co/MyHBXCcfk6 #graphs https://t.co/RKpVtkGGgs
24 days ago
It takes now less than 100 lines of code to talk to your Neo4j graph (see attached gist). This works with any database really. I used a large biomed graph but this is also arbitrary. Uses GPT3, not ChatGPT. https://t.co/vBeGneS0FO @neo4j #graphs #NLU https://t.co/WTuh8qt81r
28 days ago
JanusGraph, a Gremlin-first #GraphDatabase has a Cypher-for-Gremlin adapter enabling property #Graphs. @TSawyerSoftware has explicit visualization/analytics support. Also check the @Linkurious Ogma dataviz https://t.co/qWF36TbbSp https://t.co/qJYhhnsk93 https://t.co/cwTXhpl8u0 https://t.co/GSkeANqPCC
29 days ago
Here's the real reason why graphs are everywhere. Category Theory is the maths of mathematics and it effectively embodies the idea that #graphs can describe anything and everything. The Wolfram stack excels in this sorta stuff. @WolframResearch https://t.co/UG8rQZlQu4 https://t.co/gLpZeDlIxA
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