Fundamentals of Graph Databases Why graph databases exist, when to use them, and how they differ from relational databases. Learn nodes, edges, and relationship-first querying.

Social graphs, recommendation engines, fraud detection, dependency maps. The common thread: relationships are the data.

Learn when graph databases shine and how relationship-first storage can simplify.

jeffbailey.us/blog/2026/02...

#Graphs #GraphDatabase #Database #Software

Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship

Nang Hung Nguyen, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang, Masashi Sugiyama

Action editor: Frederic Sala

https://openreview.net/forum?id=Ey38Q882Xe

#causal #leveraging #graphs

GitHub - lalmei/puzzletree: Jigsaw solver with MSTs Jigsaw solver with MSTs. Contribute to lalmei/puzzletree development by creating an account on GitHub.

Here is the first one

github.com/lalmei/pu...

#graphs #trees #puzzle #jigsaw #MST

💻 GitHub: github.com/geometric-ke...
📄 JMLR Paper: www.jmlr.org/papers/v26/2...

#MachineLearning #GeometricDeepLearning #GaussianProcesses #Kernels #Graphs #Manifolds #JMLR #OpenSource

or, as the great mathematician Cauchy is reputed to have said: "give me five points, and I will give you an elephant..." #graphs

AC$\oplus$DC search: behind the winning solution to the FlyWire graph-matching challenge

Daniel Lee, Arie Matsliah, Lawrence K. Saul

Action editor: Giannis Nikolentzos

https://openreview.net/forum?id=8MjCOMyaDf

#neurons #graphs #optimizations

New #Survey Certification:

From Euclidean to Graph-Structured Data: A Survey of Collaborative Learning

Rémi Bourgerie, Sarunas Girdzijauskas, Viktoria Fodor

https://openreview.net/forum?id=vj9l8AjLT6

#graphs #privacy #collaborative

It's time to dive into your market's stats! 📊 Have you used a graph lately? They transform numbers into stories.

Hate math? Get someone who loves numbers and graphic design to help. (Like us!)

#MarketingMagic #DataDriven #Graphs #Storytelling #AgentMarketing #MarketStats #DirectMailMarketing

Extending Formal Verification to Sequential Circuits (U. of Bremen) Researchers from University of Bremen have released “Linear Formal Verification of Sequential Circuits using Weighted-AIGs”. ...

#Design #& #Verification #Technical #Papers #boolean […]

[Original post on semiengineering.com]

Energy flow graph showing grid and solar input and the various energy sinks in the house.

It will probably be a month or so before the house reaches the true neutral energy cost. However I had the first free tank of hot water today. About 4kWh of excess #solargeneration went into the hot water and almost 6kWh to the grid.

#graphs

Graphs and Charts Commonly Use in Research Graphs and Charts Commonly Use in Research: The four most common are probably line graphs, bar graphs and histograms, pie charts

📊Must read this important article about #Graphs and #Charts Commonly Use in #Research

📍Scatterplot

📍Bar chart

📍Line chart

📍Pie chart

📍Stacked column

📍Histogram

From #FADIC:

fadic.net/graphs-and-c...

Prompt2Chart - AI-Powered Data Visualizations Turn your data into interactive charts and visualizations with AI. Upload CSV or JSON, describe what you want to see, and get D3.js charts instantly.

I love interactive charts.
I do not love the effort required to make them.

So I built Prompt2Chart.

Paste data, describe the chart, get something interactive you can tweak.

prompt2chart.com

Would you ever use this?

#data #BI #datavisualization #d3js #charts #graphs #dataviz

a man in a blue shirt and tie is standing in front of a wall with papers on it . ALT: a man in a blue shirt and tie is standing in front of a wall with papers on it .

per month not the 328K of the Biden Era. True Trump's Numbers are extremely low but Biden's are Bullshit too. There is no Pepe Silva and he doesn't have a Job here. #Graphs

Proper Orthogonal Decomposition for Scalable Training of Graph Neural Networks

Abhishek A, Manohar Kaul, Mohit Meena, Mahesh Chandran

Action editor: Kenta Oono

https://openreview.net/forum?id=LeL6whBoWE

#sketches #sketch #graphs

The theory behind GRAs (Graph Rewriting Automata)

This is a brilliant concept blend.

Something like this is happening as we live.

paulcousin.net/graph-rewrit...

#graphs #GRA #artificiallife

Introducing RAG 2.0: Agentic RAG + Knowledge Graphs (FREE Template) In AI-driven knowledge retrieval, blending multiple strategies can create a potent mix that pushes the boundaries of how machines...

#AI #AI #development #cloud #coding #data #retrieval #FastAPI #Knowledge #Graphs #Machine […]

GraphFM: A generalist graph transformer that learns transferable representations across diverse d...

Divyansha Lachi, Mehdi Azabou, Vinam Arora, Eva L Dyer

Action editor: Ilan Shomorony

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

#graphfm #graphs #graph

Hypergraphs as Weighted Directed Self-Looped Graphs: Spectral Properties, Clustering, Cheeger Ine...

Zihao Li, Dongqi Fu, Hengyu Liu, Jingrui He

Action editor: Seungjin Choi

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

#hypergraphs #hypergraph #graphs

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs

Zihan Chen, Xingbo Fu, Yushun Dong, Jundong Li, Cong Shen

Action editor: Ying Wei

https://openreview.net/forum?id=pHii7cWco7

#federated #graphs #nodes

If you’ve run across a graph and are clear what it says, try ChartHawk: Upload a chart. See what it actually says.

(Powered by AI. Takes seconds.)

charthawk.up.railway.app

#dataviz #graphs #charts

The Missing Layer in Your AI Stack: Context, Not Just State From SQL to Semantics: The Rise of the Context Graph for AI Agents

As we move from dashboards to autonomous agents, something breaks.

Systems of record capture what happened, not why.

Why data platforms need Truth Registries + Context Graphs for the agentic era 👇
www.dataengineeringw...

#DataEngineering #AgenticAI #Graphs #LLMs

> The summer has been quite busy, and we are very thrilled to announce the release of #Gephi Lite v1.0! This marks for us the first version of #GephiLite we are really proud about.

#GraphVisualization #graphs

https://gephi.wordpress.com/2025/10/08/gephi-lite-v1/

Man and Woman, Boy and Girl Today, we will examine the performance of Man, Woman, Boy, and Girl in the Gender Census. But wait! The Gender Census is a global annual online survey of people with a gender that isn’t exclusively male or female. Doesn’t that mean Man, Woman, Boy, and Girl are wrong answers? We will begin by discussing these terms in the context of nonbinary identity, before exploring how these terms have performened in the Gender Census. We will also use a pairing analysis to determine the other words most commonly chosen by respondents who selected these terms. Discussion Most people have a gender that is either exclusively male or female. But some people have a gender that isn’t exclusively male or female, and they’re known as nonbinary. So what are Man, Woman, Boy, and Girl doing in a survey of nonbinary genders? While these terms aren’t inherently nonbinary genders, they can be part of someone’s larger nonbinary identity. You may have encountered the compound terms Nonbinary Man, Nonbinary Woman, Nonbinary Trans Man, or Nonbinary Trans Woman. One of the ways you could interpret these compound terms is that someone has a gender that’s between male and female, but closer to one side or the other. What about demiboy and demigirl? We will discuss those terms in the next article. We already have more than enough on our plate for today. For reasons I will explore in this article and the next, I consider Man, Woman, Boy, and Girl to be valid choices in the Gender Census. Examining the other words most commonly chosen by respondents who selected these terms will help determine whether or not this is true. Whether you consider these options to be right or wrong answers, within the context of the Gender Census, could affect how you interpret the results we will discuss in this article, and the ones that follow. While I believe they are correct answers, it might be worth keeping both possibilities in mind for now. First, we’ll examine the performance of Woman and Girl in the Gender Census. Next, we’ll examine the performance of Man and Boy in the survey. Then, we’ll explore the other identities most commonly chosen by respondents who selected Woman, Girl, Man, and Boy. Woman The wording of the checkbox for woman has changed several times in the Gender Census. Woman appeared as a checkbox in the Gender Census from 2015 to 2023. In 2015, “Woman” appeared as a checkbox, and “Girl” did not. From 2016 to 2019, the checkbox was “Woman (or girl if younger)”. From 2020 to 2022, Woman and Girl appeared as separate checkboxes. In 2023, “Woman” appeared as a checkbox, and “Girl” did not. Woman has appeared in the Gender Census, in one form or another, nine times. Its minimum was 10.6% in 2021, and its maximum was 15.6% in 2015. Woman’s average is 12.7%, and woman’s range is 5%. Girl Girl appeared, on its own, in the Gender Census, three times, from 2020 to 2022. In 2020, Girl received 9.1%. In 2021, Girl received 9.7%. In 2022, Girl received 11.1%. Girl’s average is 10%. Woman and Girl Woman performed better than girl in two of the three years when they appeared as separate checkbox options in the Gender Census. Girl performed better than woman in one of the three years when they appeared as separate checkboxes. In the three years girl appeared as a separate checkbox, woman was chosen by a smaller percentage of respondents than in other years. Man The wording of the checkbox for man has changed several times in the Gender Census. Man appeared as a checkbox in the Gender Census from 2015 to 2023. In 2015, “Man” appeared as a checkbox, and “Boy” did not. From 2016 to 2019, the checkbox was “Man (or boy if younger)”. From 2020 to 2022, Man and Boy appeared as separate checkboxes. In 2023, “Man” appeared as a checkbox, and “Boy” did not. Man has appeared in the Gender Census, in one form or another, nine times. Man’s minimum was 7.6% in 2016. Man’s maximum was 16.1% in 2023. Man’s average is 10.5%, and Man’s range is 8.5%. Boy Boy appeared as a checkbox, on its own, in the Gender Census, three times, from 2020 to 2022. In 2020, Boy received 9.5%. In 2021, Boy received 11%. In 2022, Boy received 14.7%. Boy’s average is 11.7%. Boy and Man Boy was chosen by a larger percentage of respondents than Man in the three years the terms appeared separately in the Gender Census. All Together Now Now, let’s compare the performance for Man, Woman, Boy, and Girl, all on a single graph. All four terms have consistently received between 7% and 17% in the Gender Census. Man has both the lowest minimum and the largest maximum, among the four terms. Boy performed better than Girl in each of the three years they appeared in the survey. Woman outperformed Man seven times, from 2015 to 2021. Man outperformed Woman twice, in 2022 and 2023. Woman Pairing Analysis Next, let’s examine the terms that were most commonly chosen by respondents who also selected Women in the 2023 Gender Census, the last time Woman appeared as a checkbox. 56.1% of Woman respondents identified as queer. 54.1% of Woman respondents identified as nonbinary. Therefore, majorities of Woman respondents identified as queer and nonbinary. 44% of Woman respondents identified as, “a person / human / [my name] / ‘I’m just me.’” 43.2% of Woman respondents identified as gender non-conforming. 40.6% of Woman respondents identified as trans. Therefore, large minorities of Woman respondents identified as “a person…”, gender non-conforming, and trans. Woman respondents were less likely than Gender Census respondents as a whole to identify as nonbinary and trans. Girl Pairing Analysis Next, let’s examine the terms most commonly chosen by respondents who also selected Girl in the 2022 Gender Census, the most recent survey where it appeared as a checkbox. 62% of Girl respondents identified as queer. 60.3% of Girl respondents identified as nonbinary. Therefore, majorities of Girl respondents identified as queer and nonbinary. 47% of Girl respondents identified as women. 44.6% of Girl respondents identified as trans. 40.9% of Girl respondents identified as transgender. 40.4% of Girl respondents identified as gender non-conforming. Therefore, large minorities of Girl respondents identified as women, trans, transgender, and gender non-conforming. Girl respondents were significantly more likely to identify as women than Gender Census respondents as a whole. Girl respondents were less likely to identify as nonbinary than Gender Census respondents as a whole. Man Pairing Analysis Now, let’s examine the terms most likely to be chosen by respondents who also selected Man in the 2023 Gender Census, the most recent survey where it appeared as a checkbox. 72.6% of Man respondents identified as trans. 68.1% of Man respondents identified as transgender. 65.7% of Man respondents identified as transmasculine. 60.1% of Man respondents identified as queer. 54% of Man respondents identified as nonbinary. Therefore, majorities of Man respondents identified as trans, transgender, transmasculine, queer, and nonbinary. 49.6% of man respondents identified as gender non-conforming. 41.5% of man respondents identified as fags. 40.4% of man respondents selected “a person / human / [my name] / ‘I’m just me.’ ” Therefore, large minorities of man respondents identified as gender non-conforming, fags, and “a person…” Man respondents were significantly more likely to identify as transmasculine, transgender, trans, and fags, than Gender Census respondents as a whole. Man respondents were less likely to identify as nonbinary and “a person…” than Gender Census respondents as a whole. Boy Pairing Analysis Now, let’s examine the terms most commonly selected by respondents who also selected Boy in the 2022 Gender Census, the last survey where it appeared as a checkbox. 68.8% of Boy respondents identified as trans. 66.5% of Boy respondents identified as transmasculine. 65.8% of Boy respondents identified as queer. 65.3% of Boy respondents identified as nonbinary. 64.5% of Boy respondents identified as transgender. 51.8% of Boy respondents identified as gender non-conforming. Therefore, majorities of Boy respondents identified as trans, transmasculine, queer, nonbinary, transgender, and gender non-conforming. 44.8% of Boy respondents identified as men. 40.8% of Boy respondents identified as genderqueer. Therefore, large minorities of Boy respondents identified as men and genderqueer. Boy respondents were significantly more likely to identify as transmasculine, men, trans, and transgender, than Gender Census respondents as a whole. What have we learned? Now, let’s revisit the question we asked at the beginning of this article. Are Man, Woman, Boy, and Girl wrong answers, for the purposes of the Gender Census? While these terms are not, in and of themselves, nonbinary identities, I maintain that they can be part of someone’s larger nonbinary identity, when included alongside other identity terms. In 2023, majorities of Man and Woman respondents, in the Gender Census, identified as nonbinary. In 2022, more than 60% of Boy and Girl respondents, in the Gender Census, identified as nonbinary. Moreover, the percent of respondents, who chose each of these four terms, who identified as nonbinary, wasn’t substantially different from the percent of Gender Census respondents, as a whole, who identified as nonbinary. To me, this shows the people selecting these terms in the survey are not, by and large, binary men and women who are incorrectly completing a survey that is meant to answer questions about people with non-binary genders. Nevertheless, we will revisit this question, in the next article, with additional data. Because once again, whether you interpret these to be “wrong” answers, in the context of the survey, will affect how you interpret the survey’s results. Woman and Man, have appeared in the Gender Census, in one form or another, nine times. Girl and Boy have appeared in the Gender Census, on their own, three times. Woman’s average is 12.7%. Boy’s average is 11.7%. Man’s average is 10.5%. Girl’s average is 10%. This means that all four of these terms have, on average, outperformed many other terms in the Gender Census, including all of the terms shown in the graph below. The surprising fact that Man, Woman, Boy, and Girl outperform many nonbinary identities, even among nonbinary people, is an interesting result, and not one that everyone would necessarily predict. If you believe these results are the consequence of many people completing the survey, who were not the intended target population of the survey, then this result might not be meaningful. But if you believe, based on the other terms selected by Man, Woman, Boy, and Girl respondents, that these are legitimate choices chosen by nonbinary people, this result is a meaningful one. Respondents who selected Man or Boy were more likely to identify as trans, and more likely to identify as transgender, than respondents who selected Woman or Girl. These comparisons will be the focus of a future article, which will contain similar results for demiboy and demigirl, as well. Another future article will discuss the terms, including Man and Boy, that have a majority of respondents who selected transmasculine. These terms are part of the Transmasculine Family Tree. In the next article, we will examine the performance of demiboy and demigirl in the Gender Census, explore the other terms those respondents were most likely to select in the survey, and compare their performance to the terms we discussed today. So make sure to join me next time, as we continue to explore LGBT identity, by the numbers.

This ongoing thread can be read as an article on my blog, Meticulous Musings.

jasonbeets.blogspot.com/2026/01/man-and-woman-bo...

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#Man #Woman #Boy #Girl #Men #Women #Boys #Girls #Nonbinary #Gender #Survey #LGBT #Queer #Writing #Blog #Analysis #Graphs

Learning to Rank Features to Enhance Graph Neural Networks for Graph Classification

Fouad Alkhoury, Tamas Horvath, Christian Bauckhage, Stefan Wrobel

Action editor: Vicenç Gomez

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

#graphs #graph #ranking

Tree Structure for the Categorical Wasserstein Weisfeiler-Lehman Graph Kernel

Keishi Sando, Tam Le, Hideitsu Hino

Action editor: Rémi Flamary

https://openreview.net/forum?id=VwoSsFK22P

#graphs #tree #graph

New #J2C Certification:

The Confusion is Real: GRAPHIC - A Network Science Approach to Confusion Matrices in Deep Learning

Johanna S. Fröhlich, Bastian Heinlein, Jan U. Claar et al.

https://openreview.net/forum?id=UP9bx1WJwR

#classifiers #visualize #graphs

TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scen...

New #TMLR-Paper-with-Video:

TESGNN: Temporal Equivariant Scene Graph Neural Networks for Efficient and Robust Multi-View 3D Scen...

Pham Phuoc Minh Quang, Nguyen Tiet Nguyen Khoi, Ngo Chi Lan et al.

https://tmlr.infinite-conf.org/paper_pages/boM0kkYPzE

#graphs #networks #3d

Learning to Rank Features to Enhance Graph Neural Networks for Graph Classification

New #TMLR-Paper-with-Video:

Learning to Rank Features to Enhance Graph Neural Networks for Graph Classification

Fouad Alkhoury, Tamas Horvath, Christian Bauckhage, Stefan Wrobel

https://tmlr.infinite-conf.org/paper_pages/WmZGvWRAWb

#graphs #graph #networks

Line chart of U.S. food inflation since 2020 showing a 2022 peak, sharp cooldown in 2023, and data gap during the 2025 shutdown.

🚨U.S. inflation remains at 2.7% in December as food prices post biggest jump in 3 years

Details here: wp.me/p3AV1k-2O1

Data caveat : wp.me/p3AV1k-2Mt

#econsky #datavisuals #data #inflation #breakingnews #graphs #USinflation