Tootfinder

google_plus: Google (2013)
Snapshot of connections among users of Google , collected in 2012. Nodes are users and a directed edge (i,j) represents user i added user j to i's circle.
This network has 211187 nodes and 1506896 edges.
Tags: Social, Online, Unweighted
https://networks.skewed.de/net/google_

citeulike: CiteULike
Three bipartite networks that make up the CiteULike folksonomy, representing the tag-publication, user-publication, and user-tag networks. The date of this snapshot is uncertain.
This network has 885046 nodes and 2411819 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
https://

This https://arxiv.org/abs/2501.01299 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Model Reduction for Transport-Dominated Problems via Cross-Correlation Based Snapshot Registration
Traditional linear approximation methods, such as proper orthogonal decomposition and the reduced basis method, are ill-suited for transport-dominated problems due to the slow decay of the Kolmogorov $n$-width, leading to inefficient and inaccurate reduced-order models. In this work, we propose a model reduction approach for transport-dominated problems by employing cross-correlation based snapshot registration to accelerate the Kolmogorov $n$-width decay, thereby enabling the construction of e…

visualizeus: vi.sualize.us picture tagging network
Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.
This network has 577437 nodes and 2298816 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph

This https://arxiv.org/abs/2505.11197 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schrödinger Bridge
Modeling the dynamics from sparsely time-resolved snapshot data is crucial for understanding complex cellular processes and behavior. Existing methods leverage optimal transport, Schrödinger bridge theory, or their variants to simultaneously infer stochastic, unbalanced dynamics from snapshot data. However, these approaches remain limited in their ability to account for cell-cell interactions. This integration is essential in real-world scenarios since intercellular communications are fundamen…

lkml_reply: Linux kernel reply network
A network of replies among email address found on the Linux kernel mailing list. Nodes are email addresses and each directed edge represents a reply from email address i to email address j. The date of this snapshot is uncertain.
This network has 63399 nodes and 1096440 edges.
Tags: Social, Communication, Unweighted, Multigraph, Timestamps

This https://arxiv.org/abs/2502.00514 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A Proof of The Changepoint Detection Threshold Conjecture in Preferential Attachment Models
We investigate the problem of detecting and estimating a changepoint in the attachment function of a network evolving according to a preferential attachment model on $n$ vertices, using only a single final snapshot of the network. Bet et al.~\cite{bet2023detecting} show that a simple test based on thresholding the number of vertices with minimum degrees can detect the changepoint when the change occurs at time $n-Ω(\sqrt{n})$. They further make the striking conjecture that detection becomes im…

Exact operator inference with minimal data
Henrik Rosenberger, Benjamin Sanderse, Giovanni Stabile
https://arxiv.org/abs/2506.01244 https://

Exact operator inference with minimal data
This work introduces a novel method to generate snapshot data for operator inference that guarantees the exact reconstruction of intrusive projection-based reduced-order models (ROMs). To ensure exact reconstruction, the operator inference least squares matrix must have full rank, without regularization. Existing works have achieved this full rank using heuristic strategies to generate snapshot data and a-posteriori checks on full rank, but without a guarantee of success. Our novel snapshot dat…

academia_edu: Academica.edu (2011)
Snapshot of the follower relationships among users of academia.edu, a platform for academics to share research papers, scraped in 2011. Nodes are users and a directed edge (i,j) denotes that user i follows j.
This network has 200169 nodes and 1398063 edges.
Tags: Social, Online, Unweighted
https://

Look at a snapshot
A moment frozen in time
Never seen again.
#dailyhaikuprompt - snapshot
#haiku
#poem

U.S. Multifamily Market Snapshot — May 2025
Arbor - May 14, 2025
“Examining key benchmarks for the sector, the multifamily market’s consistent performance provides a solid foundation for continued expansion despite broader economic uncertainties, while well-positioned multifamily investors consider new opportunities.”
#ArborRealtyTrust

U.S. Multifamily Market Snapshot — May 2025
The U.S. multifamily market continued to settle into a normalized cycle, despite ongoing uncertainties surrounding the global economy and labor market. There is a rising tide of optimism for the sector ahead and investors are continuing to take advantage of market opportunities.

marker_cafe: The Marker Cafe (2011)
Snapshot of connections among users of the Israeli social network Marker Cafe, collected in 2011. Nodes are users and a directed edge (i,j) represents user i added user j to i's circle.
This network has 69413 nodes and 1644849 edges.
Tags: Social, Online, Unweighted
https://

Deep learning of thermodynamic laws from microscopic dynamics
Hiroto Kuroyanagi, Tatsuro Yuge
https://arxiv.org/abs/2506.01506 https://

Deep learning of thermodynamic laws from microscopic dynamics
We numerically show that a deep neural network (DNN) can learn macroscopic thermodynamic laws purely from microscopic data. Using molecular dynamics simulations, we generate the data of snapshot images of gas particles undergoing adiabatic processes. We train a DNN to determine the temporal order of input image pairs. We observe that the trained network induces an order relation between states consistent with adiabatic accessibility, satisfying the axioms of thermodynamics. Furthermore, the int…

This https://arxiv.org/abs/2411.10877 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Developer Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development
Despite the utility that Generative AI (GenAI) tools provide for tasks such as writing code, the use of these tools raises important legal questions and potential risks, particularly those associated with copyright law. As lawmakers and regulators engage with those questions, the views of users can provide relevant perspectives. In this paper, we provide: (1) a survey of 574 developers on the licensing and copyright aspects of GenAI for coding, as well as follow-up interviews; (2) a snapshot of…

This https://arxiv.org/abs/2412.12187 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Random walk based snapshot clustering for detecting community dynamics in temporal networks
The evolution of many dynamical systems that describe relationships or interactions between objects can be effectively modeled by temporal networks, which are typically represented as a sequence of static network snapshots. In this paper, we introduce a novel random walk-based approach that can identify clusters of time-snapshots in which network community structures are stable. This allows us to detect significant structural shifts over time, such as the splitting or merging of communities or …

Information-theoretic machine learning for time-varying mode decomposition of separated airfoil wakes
Kai Fukami, Ryo Araki
https://arxiv.org/abs/2505.24132

Information-theoretic machine learning for time-varying mode decomposition of separated airfoil wakes
We perform an information-theoretic mode decomposition for separated wakes around a wing. The current data-driven approach based on a neural network referred to as deep sigmoidal flow enables the extraction of an informative component from a given flow field snapshot with respect to a target variable at a future time stamp, thereby capturing the causality as a time-varying modal structure. We consider three examples of separated flows around a NACA0012 airfoil, namely, 1. laminar periodic wake …

as_skitter: Skitter IP graph (2005)
An aggregate snapshot of the Internet Protocol (IP) graph, as measured by the traceroute tool on CAIDA's skitter infrastructure, in 2005.
This network has 1696415 nodes and 11095298 edges.
Tags: Technological, Communication, Unweighted
https://networks.skewed.de/net/as_s…

discogs_label: Discogs label affiliations
Two bipartite networks of the affiliations between musical labels and either musical genres or musical "styles," as given in the discogs.com database. Edges represent that a label was involved in a production of a musical release of a given genre or given style. The date of this snapshot is uncertain.
This network has 270786 nodes and 4147665 edges.
Tags: Informational, Relatedness, Unweighted, Multigraph

The last coffee in my favorite neighborhood spot in #Hanoi. 👋❤️
I will miss the Vietnamese vibe

marker_cafe: The Marker Cafe (2011)
Snapshot of connections among users of the Israeli social network Marker Cafe, collected in 2011. Nodes are users and a directed edge (i,j) represents user i added user j to i's circle.
This network has 69413 nodes and 1644849 edges.
Tags: Social, Online, Unweighted
https://

anybeat: Anybeat social network (2013)
A snapshot of the Anybeat online social network from 2013, before it was shut down. Nodes are users and links represent friendships. The edge direction (i, j) denotes the user i follows user j.
This network has 12645 nodes and 67053 edges.
Tags: Social, Online, Unweighted
https://ne…

PSA: In case you run #Ubuntu 24.10 with #ZFS on Root, DO NOT TRY TO UPGRADE YET! You are very likely to run into a #Linux kernel deadlock mid-flight during the upgrade which leaves you with a broken system. …

System deadlock during Ubuntu upgrade 24.10→25.04 with ZFS root due to update-grub calling `ls /.zfs/snapshot/…` via `10_linux_zfs` causing kernel lock at mount.zfs · Issue #17337 · openzfs/zfs
System information Type Version/Name Distribution Name Ubuntu Distribution Version 24.10 Kernel Version 6.11.0-25-generic Architecture x86_64 OpenZFS Version zfs-2.2.6-1ubuntu1.1, zfs-kmod-2.2.6-1u...

facebook_organizations: Within-organization Facebook friendships (2013)
Six networks of friendships among users on Facebook who indicated employment at one of the target corporation. Companies range in size from small to large. Only edges between employees at the same company are included in a given snapshot.
This network has 165 nodes and 726 edges.
Tags: Social, Online, Unweighted

dbpedia_location: DBpedia entity-location network
A bipartite network of the affiliations between named entities from Wikipedia and particular notable locations, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 225498 nodes and 293697 edges.
Tags: Informational, Relatedness, Unweighted

facebook_organizations: Within-organization Facebook friendships (2013)
Six networks of friendships among users on Facebook who indicated employment at one of the target corporation. Companies range in size from small to large. Only edges between employees at the same company are included in a given snapshot.
This network has 1429 nodes and 32876 edges.
Tags: Social, Online, Unweighted

google_plus: Google (2013)
Snapshot of connections among users of Google , collected in 2012. Nodes are users and a directed edge (i,j) represents user i added user j to i's circle.
This network has 211187 nodes and 1506896 edges.
Tags: Social, Online, Unweighted
https://networks.skewed.de/net/google_

google_plus: Google (2013)
Snapshot of connections among users of Google , collected in 2012. Nodes are users and a directed edge (i,j) represents user i added user j to i's circle.
This network has 211187 nodes and 1506896 edges.
Tags: Social, Online, Unweighted
https://networks.skewed.de/net/google_