In this session of Andreas Lauschke's #DataScience with #Mathematica series, he provides an introduction to Dynamic Programming for the data scientist. Watch the video, consisting of theory and illustrative examples, here:

https://youtu.be/MZnOL17CHdY

How does individual cognition influence collective behavior?

https://t.co/0ref9WD08Q https://t.co/OAesHffzcJ

https://www.pnas.org/content/early/2020/07/14/1920554117

💡 https://www.quantamagazine.org/what-is-an-individual-biology-seeks-clues-in-information-theory-20200716/

Simplicial complexes and dynamics - G. Bianconi - SIFS Colloquium https://t.co/S6ZWDGgy58

💉 https://twitter.com/UniofOxford/status/1285210154984710145?s=19

چهارشنبه ساعت۱۸:۳۰ به وقت تهران

What don’t we know about #machinelearning? Dive in with this Joint ICTP-SISSA Online Colloquium tomorrow, 22 July, at 16:00 CET!

Here’s all the info & how to join in 🎥 https://t.co/6VxNZLoy69

The Unreasonable Effectiveness of Mathematics in the Natural Sciences is an essay about mathematical concepts and their applicability written by Nobel Prize winning physicist Eugene Wigner.

It's a great read: https://t.co/7Vivp1iQaH

A great paper for your summer reading list 📚 https://t.co/4AYy4AZI9k

We have several frontend engineer positions open.
We'd prefer to get at least one senior, but if you feel you are more a mid-level you're also welcome :)

https://careers.deliveryhero.com/global/en/job/JR0000628/Senior-Frontend-Engineer-Marketing-Tech-f-m-d

#deliveryhero #frontend #javascript #berlin

🎞 Football is becoming boring? A Network Science Approach by Taha Yasseri at IC2S2 2020.

https://youtu.be/oQRxOGdQ2Fw

Pre-print: Maimone, V. M., & Yasseri, T. (2019). Football is becoming boring; Network analysis of 88 thousands matches in 11 major leagues. arXiv preprint arXiv:1908.08991.

Controlling a complex system near its critical point via temporal correlations

https://www.nature.com/articles/s41598-020-69154-0

Here we test whether the time correlation properties allow systems exhibiting a phase transition to self-tune to their critical point. We describe results in three models: the 2D Ising ferromagnetic model, the 3D Vicsek flocking model and a small-world neuronal network model. We demonstrate that feedback from the autocorrelation function of the order parameter fluctuations shifts the system towards its critical point.

🛠 JuliaCon 2020 https://t.co/ueQZfLoI8L

JuliaCon tutorials start today.

"Julia has become the fastest-growing language for computational science, and many of the top numerical researchers recently adopted it and joined the worldwide collaboration."

Doing Scientific Machine Learning (SciML) With Julia

07/26/2020, 5:00 PM — 8:30 PM GMT+3
Chris Rackauckas

Scientific machine learning combines differentiable programming, scientific simulation (differential equations, nonlinear solvers, etc.), and machine learning (deep learning) in order impose physical constraints on machine learning and automatically learn biological models. Given the composibility of Julia, many have noted that it is positioned as the best language for this set of numerical techniques, but how to do actually "do" SciML? This workshop gets your hands dirty.

🔴 مدرسه تابستانی هوش مصنوعی
🔵 پژوهشگاه دانش‌های بنیادی
⏱ مهلت ثبت‌نام: ۲۶ ژوئیه

https://cs.ipm.ac.ir/asoc2020/

🆑 ipmturin
🆔 turin.ipm.ir

Can A.I. make music? Can it feel excitement and fear? Is it alive? Will.i.am and Mark Sagar push the limits of what a machine can do. How far is too far, and how much further can we go?

https://youtu.be/UwsrzCVZAb8

#SARSCoV2
https://t.co/eFGieP4cos

Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications

Nassim Nicholas Taleb
https://www.researchers.one/article/2020-01-21.

The book investigates the misapplication of conventional statistical techniques to fat tailed distributions and looks for remedies, when possible.
Switching from thin tailed to fat tailed distributions requires more than "changing the color of the dress". Traditional asymptotics deal mainly with either n=1 or n=∞, and the real world is in between, under of the "laws of the medium numbers" --which vary widely across specific distributions. Both the law of large numbers and the generalized central limit mechanisms operate in highly idiosyncratic ways outside the standard Gaussian or Levy-Stable basins of convergence.

Six months into the pandemic, #coronavirus has reached almost every country in the world – but there’s a lot scientists still don’t know. https://t.co/ElytJd3EMQ

💡 Ecology of Intelligence - A talk with Frank Wilczek
https://www.edge.org/conversation/frank_wilczek-ecology-of-intelligence