Come join us to discuss how not to construct #functional #brain #networks! We will talk about nodes and links definitions.


17.11.2020 at 10AM EET
https://aalto.zoom.us/j/67072679004

How to attend the seminar? Check https://bit.ly/3euKzvE

💰 #PhD positions in Advanced Machine Learning at Cambridge
Application deadline: noon December 3, 2020.
Details about the application process can be found here:
https://t.co/2SwKfm9V8k

📺 https://m.youtube.com/watch?feature=emb_rel_pause&v=L6CqqlILBCI

💰 Networks, embeddings, dynamics. If that sounds exciting to you, and if you're also searching for a #postdoc, Come and work on a (super cool) project: https://t.co/xwc3jP5l0s

💰 Two interesting opportunities for #PhD/#Postdoc at the Informatics Institute, University of Amsterdam!
https://t.co/bEuil6N7KG

Check also: https://t.co/JrxtuMJDV9

👩🏻‍💻 https://brianzhang01.github.io/2018/04/distributions-with-sympy/

🦠 از کجا بفهمیم که داریم کرونا رو شکست میدیم؟

بر خلاف آمار روزانه‌ای که شبکه‌های خبری میدن، که اصلا معلوم نمی‌کنه قراره در آینده چه اتفاقی بیافته، در این ویدیو یاد می‌گیریم که
چطور از ریاضیات و نمودارهای لگاریتمی میشه کمک گرفت تا آینده‌ای که پیش رو داریم رو روشن‌تر ببینیم و قدرت تحلیل و تصمیم‌گیریمون رو بالا ببریم، نتایج تصمیمات مختلف کشورها رو به روشنی ببینیم و حدس بزنیم که «کی قراره کرونا رو شکست بدیم؟»

🔗 sitpor.org/1399/08/beating-covid-19

#ما_کرونا_را_شکست‌‌_می‌دهیم
~~~~~~
@sitpor
‌instagram.com/sitpor_media
~~~~~~~

🦠 حالا که رستوران‌ها در رتبه اول در پخش بیماری هستن، چه راه‌کاری برای کاهش شیوع کرونا وجود داره؟

https://www.nature.com/articles/d41586-020-03140-4

💉 واکسن معرفی شده توسط BioNTech از یک فناوری جدید استفاده می‌کنه که به رِنای پیام‌رسان مربوطه.

بیشتر بخونید:

Nanomedicine comes of age with mRNA vaccines

💾 New review article in Nature Reviews Physics: "Topological methods for data modelling" (by Gunnar Carlsson):

https://t.co/16PD6hriSo

Evolutionary Surrogate-assisted Prenoscription

How does machine learning help in decision-making and optimizing non-pharmaceutical interventions against Covid19

Risto Miikkulainen
Professor of Computer Science
The University of Texas at Austin and Cognizant Technology Solutions

Thursday 19 November at 18:00-19:30
Register! by 16 November at https://webropol.com/ep/HDLS-19112020

Abstract
How can we make good decisions in business, engineering design, science, education, and indeed in life in general? Good decisions are often based on experience: recalling what decisions were made in similar situations in the past, how well they worked out, and modifying them to achieve good outcomes in current situation. Evolutionary Surrogate-assisted Prenoscription (ESP) is a machine learning technology that makes it possible to come up with good decision strategies automatically. The idea is to use historical data to build a predictive surrogate model, and population based search (i.e. evolutionary computation) to discover good decision strategies against it. I’ll review the technology and evaluate it in several examples, including optimizing behavior in sequential decision tasks, and optimizing non-pharmaceutical interventions in the COVID-19 pandemic. The method is found to be sample efficient and creative, forming a foundation for optimizing many decision tasks in the future.

“The Hitchhiker's Guide to #CondensedMatter and #StatisticalPhysics” is a series of virtual events that will provide a roadmap of current research directions in the field.

🔹 Register to the first virtual school on #MachineLearning for CM by November 30: http://indico.ictp.it/event/9471/

💉 Moderna COVID-19 vaccine: two press releases one for Primary Efficacy Endpoint and one Shelf Life & Refrigerated Temperatures

1⃣ https://t.co/ZM2JghFk4y

2⃣ https://t.co/TZjQpYTbvF

An introduction to Quantum programming languages, overviewing some of the existing languages and the ecosystem around them

Read here: https://t.co/it55qrrbNr

💉 واکسن شرکت مدرنا با اثربخشی ۹۴/۵٪ دومین واکسن موثر تا به امروز بوده. این واکسن از ایده مشابهی با واکسن BioNTech استفاده می‌کنه که به رِنای پیام‌رسان مربوطه.


https://www.sciencemag.org/news/2020/11/just-beautiful-another-covid-19-vaccine-newcomer-moderna-succeeds-large-scale-trial

🧑🏻‍🏫 #Renormalization w3.p1 Intro to CA

«مقدمه‌ای بر بازبهنجارش»
هفته سوم: اتوماتای سلولی
قسمت اول: معرفی اتوماتای سلولی

یک اتوماتای سلولی شامل یک شبکه منظم از سلول‌های خاموش و روشن است. تحول این سلول‌ها توسط قواعد ثابتی که فقط وابسته به وضعیت قبلی آن سلول و همسایگانش است مشخص می‌شود. در این جلسه ابتدا اتوماتای سلولی را معرفی می‌کنم و به مفاهیمی چون «کامل بودن تورینگ» و «نمودارهای جابه‌جاشوند» می‌پردازم. سپس سراغ درشت-دانه‌بندی اتوماتای سلولی و مقاله ۲۰۰۴ و ۲۰۰۵ گلدنفلد می‌روم و در نهایت در مورد شبکه‌‌های بازبهنجارش بحث خواهم کرد.

🎞 ویدیو در صفحه اینستاگرام سیتپور

🔗 اطلاعات بیشتر:
sitpor.org/2019/09/renorm-week3-ca

~~~~~~
@sitpor
‌instagram.com/sitpor_media
~~~~~~~

📺 New lecture on how the diffusion equation arises from random walks.

https://t.co/5tt5Iewgaw

🦠 این‌که نتیجه آزمایش کرونای شما منفی باشه به این معنی نیست که واقعا ایمن هستید؛ ممکنه آزمان خطا داشته باشه (منفی کاذب) یا این‌که بیماری شما در مرحله اولیه غیرقابل تشخیص باشه. برای همین حتی در صورت منفی بودن نتیجه آزمایش کرونا، باز هم مراقبت‌های لازم رو انجام بدین!

👩🏻‍💻 اینجا کلی ویدیو خوب برای پایتون هست:
https://calmcode.io/

The scales of human mobility

Laura Alessandretti, Ulf Aslak & Sune Lehmann

Nature volume 587, pages402–407(2020)

Abstract
There is a contradiction at the heart of our current understanding of individual and collective mobility patterns. On the one hand, a highly influential body of literature on human mobility driven by analyses of massive empirical datasets finds that human movements show no evidence of characteristic spatial scales. There, human mobility is described as scale free1,2,3. On the other hand, geographically, the concept of scale—referring to meaningful levels of denoscription from individual buildings to neighbourhoods, cities, regions and countries—is central for the denoscription of various aspects of human behaviour, such as socioeconomic interactions, or political and cultural dynamics4,5. Here we resolve this apparent paradox by showing that day-to-day human mobility does indeed contain meaningful scales, corresponding to spatial ‘containers’ that restrict mobility behaviour. The scale-free results arise from aggregating displacements across containers. We present a simple model—which given a person’s trajectory—infers their neighbourhood, city and so on, as well as the sizes of these geographical containers. We find that the containers—characterizing the trajectories of more than 700,000 individuals—do indeed have typical sizes. We show that our model is also able to generate highly realistic trajectories and provides a way to understand the differences in mobility behaviour across countries, gender groups and urban–rural areas.