Tootfinder

foursquare_global: Foursquare global check-ins (2013)
A bipartite network of users and locations, representing check-in events worldwide on Foursquare, from April 2012 to September 2013. Metadata include country, city name, city type (e.g. national capital), and vender's latitude and longitude.
This network has 3935215 nodes and 22809624 edges.
Tags: Social, Online, Unweighted, Metadata, Timestamps

Honda and Mitsubishi Corporation (not the car maker, owner of Eneco / Lichtblick in Europe among others) have joined forces in Japan for the full battery life cycle: financing, 2nd life, recycling, smart charging and #V2G, all to increase resource efficiency and reduce electrification costs for users.

Honda and MC to Establish New Company, ALTNA Co., Ltd. | Honda Global Corporate Website
Honda Global | Honda and MC to Establish New Company, ALTNA Co., Ltd.

FAILED BLUFF: how Putin tried to disrupt the Global Peace Summit: https://benborges.xyz/2024/06/17/failed-bluff-how.html

Global audiences suspicious of AI-powered newsrooms, report finds
https://poliverso.org/display/0477a01e-31ed5e32-ab073a74779cf9f9
Global audiences suspicious of AI-powered newsrooms, report findsGlobal concerns about the use of AI in news productio…

Fremantle and Pluto TV strike a global deal to launch 25 FAST channels across 13 countries, including the US, UK, Canada, Germany, Switzerland, Spain, and Italy (Etan Vlessing/The Hollywood Reporter)
https://www.hollywoodreporter.com/business

Fremantle, Pluto TV Expand FAST Channel Partnership Worldwide
Pluto TV users will get 24/7 broadcasts of ‘Baywatch,’ ‘Three’s Company,’ ‘Family Feud Classic’ and ‘Let’s Make a Deal’ across 13 new global markets.

This https://arxiv.org/abs/2405.14400 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

Verifying Global Two-Safety Properties in Neural Networks with Confidence
We present the first automated verification technique for confidence-based 2-safety properties, such as global robustness and global fairness, in deep neural networks (DNNs). Our approach combines self-composition to leverage existing reachability analysis techniques and a novel abstraction of the softmax function, which is amenable to automated verification. We characterize and prove the soundness of our static analysis technique. Furthermore, we implement it on top of Marabou, a safety analys…

Ecumenical Patriarchate signs global peace summit communique, Rwanda's signature removed: https://benborges.xyz/2024/06/18/ecumenical-patriarchate-signs.html

Lightning-Fast Thunderstorm Warnings: Predicting Severe Convective Environments with Global Neural Weather Models
Monika Feldmann, Tom Beucler, Milton Gomez, Olivia Martius
https://arxiv.org/abs/2406.09474

Lightning-Fast Thunderstorm Warnings: Predicting Severe Convective Environments with Global Neural Weather Models
The recently released suite of AI weather models can produce multi-day, medium-range forecasts within seconds, with a skill on par with state-of-the-art operational forecasts. Traditional AI model evaluation predominantly targets global scores on single levels. Specific prediction tasks, such as severe convective environments, require much more precision on a local scale and with the correct vertical gradients between levels. With a focus on the convective season of global hotspots in 2020, we …

corporate_directors: Global corporate directors (2016)
Bipartite network of directors and the companies on whose boards they sit, spanning 54 countries worldwide, constructed from data collected by the Financial Times (c. Sept. 2016). Person nodes are annotated with age and gender. Company nodes are annotated with their country, sector, industry, and number of employees.
This network has 356638 nodes and 377060 edges.
Tags: Economic, Governance, Unweighted, Metadata

Lightning-Fast Thunderstorm Warnings: Predicting Severe Convective Environments with Global Neural Weather Models
Monika Feldmann, Tom Beucler, Milton Gomez, Olivia Martius
https://arxiv.org/abs/2406.09474

Lightning-Fast Thunderstorm Warnings: Predicting Severe Convective Environments with Global Neural Weather Models
The recently released suite of AI weather models can produce multi-day, medium-range forecasts within seconds, with a skill on par with state-of-the-art operational forecasts. Traditional AI model evaluation predominantly targets global scores on single levels. Specific prediction tasks, such as severe convective environments, require much more precision on a local scale and with the correct vertical gradients between levels. With a focus on the convective season of global hotspots in 2020, we …