Complex Systems Studies

We're looking for a computational neuroscience #PhD student to start Sept 22. The student will use recurrent neural network models and analysis of neural population data from mice to ask "why are sensory symptoms common in autism?" More info here: https://t.co/o0tw7j3r6X

In this talk I will review the chronology of my works trying to find some logical explanation for the sequence of works I have done. https://t.co/A3ROIMgaEN

🦠💉 Seriously, how much vaccination is enough to reach herd immunity? How does the expected epidemic size depend on homophily in vaccine adoption? 🔗 arxiv.org/abs/2112.07538. 1) We find that already a small level of homophily (h) can considerably increase the critical vaccine coverage (πᶜᵥ) required for herd immunity and that stronger homophily can push this threshold entirely out of reach. 2) Our framework is general enough to account for homophily by adherence to other epidemic interventions that reduce the susceptibility or infectiousness of individuals, such as #social_distancing practices, use of protective equipment, and adoption of digital #contact_tracing. 3) Vaccines' efficacy against susceptibility or transmitting the infection can vary. For perfect vacc, the epidemic size increases monotonically as a function of homophily, while for vacc with limited efficacy, the epidemic size is max. at an intermediate level of homophily.

Why can spin glasses help us understand neural systems? Because they captured the key complexities related to memory, learning, and hierarchy. It was a revolution. Check this paper by Sompolinsky in PhysicsToday #sfiscience https://t.co/x6Yq8Sahyo

CompSci - Call 2 - Marie Sklodowska-Curie #PhD Fellowships in Natural Sciences - 17 positions The CompSci doctoral programme will train a new generation of natural science researchers with a foundation in computational methods - providing them with the knowledge, skills and vision to digitally transform the European education, research, government and industry sectors. https://www.jobbnorge.no/en/available-jobs/job/214258/compsci-call-2-marie-sklodowska-curie-phd-fellowships-in-natural-sciences-17-positions

#phd Sam Hamels https://biblio.ugent.be/person/802000900823

📌دانشکده فیزیک میزگردی تدارک دیده است با عنوان " پدیدار شدگی" (emergence). این میزگرد الزاما مخصوص افراد متخصص نیست و همچنین به صورت سخنرانی از پیش آماده شده نیست و با بحث و گفتگو بین برخی اساتید پیش می رود. 📆۱۷/آذر/۱۴۰۰ ⏰۱۶:۳۰-۱۸ لینک برگذاری: https://vc.sharif.edu/ch/physics-research-day

Highlights of 2021: What human mobility data tell us about COVID-19 spread. #lau_retti discusses the challenges of linking data on human travel and #covid spreading - and what new datasets & analysis can tell us 🔓FREE to read: https://t.co/GH0J8XOhie

دوشنبه ۸ شب https://www.clubhouse.com/event/PQRKJBv8

Evolution of cooperation in costly institutions exhibits Red Queen and Black Queen dynamics in heterogeneous public goods https://doi.org/10.1038/s42003-021-02865-w Public goods are often subject to heterogeneous costs, such as the necessary costs to maintain the public goods infrastructure. However, the extent to which heterogeneity in participation cost can affect groups’ ability to provide public goods is unclear. Here, by introducing a mathematical model, I show that when individuals face a costly institution and a free institution to perform a collective action task, the existence of a participation cost promotes cooperation in the costly institution. Despite paying for a participation cost, costly cooperators, who join the costly institution and cooperate, can outperform defectors who predominantly join a free institution. This promotes cooperation in the costly institution and can facilitate the evolution of cooperation in the free institution. For small profitability of the collective action, cooperation in a costly institution but not the free institution evolves. However, individuals are doomed to a winnerless red queen dynamics in which cooperators are unable to suppress defection. For large profitabilities, cooperation in both the costly and the free institution evolves. In this regime, cooperators with different game preferences complement each other to efficiently suppress defection in a black queen dynamic.

⭕️ سمینار‌های فیزیک آماری ⭕️ 💡 موضوع ارائه: ظهور همکاری در بازی‌های تکاملی ناهمگون و پرهزینه 🗣 ارائه دهنده: محمد سلحشور (موسسه ماکس پلانک لایپزیک) 📅 زمان ارائه: یک‌شنبه ۱۴ آذر ساعت ۱۵:۰۰ 🚪 محل برگزاری: 🔗 اتاق مجازی گروه فیزیک آماری 💢#اطلاع_رسانی_سمینارهای_دانشکده 💢#سمینار_فیزیک_آماری 💢#دکتر_مقیمی #دکتر_قنبرنژاد #دکتر_روحانی 🆔 @anjoman_elmi_phys_sut

"The Physics of Machine Learning: An Intuitive Introduction for the Physical Scientist" (by Stephon Alexander, Sarah Bawabe, Batia Friedman-Shaw, Michael W. Toomey): https://t.co/yXX2CBbM9n "This article is intended for physical scientists who wish to gain deeper insights into machine learning algorithms which we present via the domain they know best, physics."

Our next seminar is coming soon! Topic? Consciousness 🤯 When? 16.12.2021, 16:00 (EET) More info: https://t.co/Ysn0q5oV9F Looking forward to seeing you then!

a Twitter thread from tiagopeixoto https://telegra.ph/a-Twitter-thread-from-tiagopeixoto-12-02

موضوع سخنرانی: رویکرد فیزیک آماری به سیستم‌های پيچيده؛ نوبل فیزیک ۲۰۲۱ سخنران: دکتر افشین منتخب - دانشیار فیزیک دانشگاه شیراز و پژوهشگر فیزیک آماری، سیستم‌های پیچیده و شبکه‌های عصبی برگزار شده در گروه اِروتِسی @Quaestio

سخنرانی لایو در انجمن علمی‌ اروتسی #موضوع_سخنرانی: رویکرد فیزیک آماری به سیستم‌های پيچيده؛ نوبل فیزیک ۲۰۲۱ #سخنران: دکتر افشین منتخب - دانشیار فیزیک دانشگاه شیراز و پژوهشگر فیزیک آماری، سیستم‌های پیچیده و شبکه‌های عصبی #زمان: سه‌شنبه ۹ آذر ۱۴۰۰ ساعت ۲۲ به وقت ایران #مکان: گروه علمی اِروتِسی کانال تلگرامیِ انجمن اروتسی به نشانیِ Quaestio@

Interested in doing a #PhD in #MachingLearning #MPI_IS and #CambridgeMLG? We offer a great collaborative fellowship where you spend one year at one institution and 3 years at the other. Apply until December 1, 2021! https://t.co/nvVWAdrlNf #Tübingen #Cambridge #AI

International School and Conference on Network Science, NetSci-X 2022 -Porto, Portugal February 8-11, 2022 Deadline for abstracts: December 3th https://t.co/gQJHtLgkRI