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.
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.
🎞 Understanding Epidemics: The SIR Model and COVID-19
https://www.youtube.com/watch?v=72kLBDiy0h0&feature=youtu.be
https://www.youtube.com/watch?v=72kLBDiy0h0&feature=youtu.be
YouTube
Understanding Epidemics: The SIR Model and COVID-19
In this video, I describe the SIR model of epidemics, how it produces exponential growth, and how it reveals a "tipping point" in whether diseases spread bas...
Forwarded from Sitpor.org سیتپـــــور
🕸 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
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
ML glasses.jpeg
1013 KB
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
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
🥁 Don't miss the online course "Machine Learning", geared towards graduate level physics students
https://t.co/6G9G3ZywSL
PERIMETER INSTITUTE RECORDED SEMINAR ARCHIVE
https://t.co/6G9G3ZywSL
PERIMETER INSTITUTE RECORDED SEMINAR ARCHIVE
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
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
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/
https://fastgrants.org/
fastgrants.org
Fast Grants
Funding for scientists at academic institutions working on COVID-19 related projects.
💰 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
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
Complex Systems Studies
Network Epidemiology Online Workshop Series Join us for Understanding and Exploring Network Epidemiology in the Time of Coronavirus, a special online workshop series presented by the University of Maryland’s COMBINE program in network biology in partnership…
YouTube
Net-COVID Session1A: Network Epidemiology Tutorial by Laurent Hebert-Dufresne
First tutorial of the Net-COVID online series: Understanding and Exploring Network Epidemiology in the Time of Coronavirus. Lecture by Laurent Laurent Hebert-Dufresne from the University of Vermont. See go.umd.edu/net-covid for more information about the…
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
RIP John Horton Conway
https://amp.theguardian.com/science/2015/jul/23/john-horton-conway-the-most-charismatic-mathematician-in-the-world
the Guardian
John Horton Conway: the world’s most charismatic mathematician
The long read: John Horton Conway is a cross between Archimedes, Mick Jagger and Salvador Dalí. For many years, he worried that his obsession with playing silly games was ruining his career – until he realised that it could lead to extraordinary discoveries
Complex Systems Studies
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
Quanta Magazine
A Life in Games
The mathematician John Horton Conway’s myriad accomplishments — including the Game of Life, sprouts and the surreal numbers — are the product of a mind at play.
Complex Systems Studies
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
علت فوت جان کانوی گویا کرونا بوده:
https://dailyvoice.com/new-jersey/mercer/obituaries/covid-19-kills-renowned-princeton-mathematician-game-of-life-inventor-john-conway-in-3-days/786461/
https://dailyvoice.com/new-jersey/mercer/obituaries/covid-19-kills-renowned-princeton-mathematician-game-of-life-inventor-john-conway-in-3-days/786461/
Mercer Daily Voice
COVID-19 Kills Renowned Princeton Mathematician, 'Game Of Life' Inventor John Conway In 3 Days
Renowned mathematician and Princeton University professor John Horton Conway died April 11 of coronavirus. He was 82 .Princeton scientist Sam Wang in mourning Conway's death noted his fever started Wednesday morning. Three days later, he d…
💫 on topological data analysis (TDA) for young readers:
"Connecting the Dots: Discovering the “Shape” of Data"
https://osf.io/preprints/socarxiv/7qd4t/
"Connecting the Dots: Discovering the “Shape” of Data"
https://osf.io/preprints/socarxiv/7qd4t/