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What's up in Complexity Science?! Check out here: @ComplexSys #complexity #complex_systems #networks #network_science 📨 Contact us: @carimi
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💫 on topological data analysis (TDA) for young readers:
"Connecting the Dots: Discovering the “Shape” of Data"
https://osf.io/preprints/socarxiv/7qd4t/
متاسفانه باخبر شدیم که جان کانوی هم از دنیا رفت. آه و افسوس از این سال ۲۰۲۰!
RIP John Horton Conway
https://amp.theguardian.com/science/2015/jul/23/john-horton-conway-the-most-charismatic-mathematician-in-the-world
💰 Are you interested in eco-evolutionary dynamics using statistical physics methods?
Do you want to work on populations in which new types constantly arise?
Join my group in South Korea as a #Postdoc.
https://t.co/NjtvqfoB1z
Fast Grants: "If you are a scientist at an academic institution currently working on a #COVIDー19 related project and in need of funding, we invite you to apply for a Fast Grant. Fast Grants are $10k-$500k and decisions are made in under 48 hours.".
https://fastgrants.org/
Modeling covid in the continental US
https://t.co/woFV85mfCt
Project is work in progress, features such as data download, interactive explorations and state projections will be added in the next days. https://t.co/2vRORjpSR8
🥁 Don't miss the online course "Machine Learning", geared towards graduate level physics students
https://t.co/6G9G3ZywSL
PERIMETER INSTITUTE RECORDED SEMINAR ARCHIVE
Machine learning glasses
Giulio Biroli
Nature Physics volume 16, pages373–374(2020)
nature.com/articles/s41567-020-0873-1
Artificial neural networks now allow the dynamics of supercooled liquids to be predicted from their structure alone in an unprecedented way, thus providing a powerful new tool to study the physics of the glass transition.
here are free shareable links to both articles: https://t.co/4f5rmvrFPR & https://t.co/8f5O6MQJob
🕸 نظریه گراف و علم شبکه
نزدیک به ۲۰ ساله که چیزی به اسم نظریه شبکه یا علم شبکه در ادبیات علمی پیدا شده. شاید نزدیکترین یا نامآشناترین نظریه به علم شبکه، نظریه گراف در ریاضیات باشه. چیزی که از زمان اویلر (۱۷۳۶) شکل گرفته و در چند قرن اخیر هم همیشه حوزهی پژوهشی برای ریاضیدونها بوده. اما این فقط ظاهر کاره...
ادامه نوشته:
🔗 http://www.sitpor.org/2020/04/graph-theory-networks/
@sitpor
🎞 Understanding Epidemics: The SIR Model and COVID-19
https://www.youtube.com/watch?v=72kLBDiy0h0&feature=youtu.be
Bridging the gap between graphs and networks
Gerardo Iñiguez, Federico Battiston, Márton Karsai
https://arxiv.org/pdf/2004.01467
Network science has become a powerful tool to describe the structure and dynamics of real-world complex physical, biological, social, and technological systems. Largely built on empirical observations to tackle heterogeneous, temporal, and adaptive patterns of interactions, its intuitive and flexible nature has contributed to the popularity of the field. With pioneering work on the evolution of random graphs, graph theory is often cited as the mathematical foundation of network science. Despite this narrative, the two research communities are still largely disconnected. In this Commentary we discuss the need for further cross-pollination between fields -- bridging the gap between graphs and networks -- and how network science can benefit from such influence. A more mathematical network science may clarify the role of randomness in modeling, hint at underlying laws of behavior, and predict yet unobserved complex networked phenomena in nature.
