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🌟🌟🌟 Еще раз поздравляем наших выпускников – победителей Конкурса публикаций 6-го потока обучения!

Со статьями победителей вы можете ознакомиться на нашем сайте

Напомним, что победителями стали выпускники 6-го потока обучения:

🔥 Митьковский Дмитрий Александрович.

Статья "Self-assembly of amphiphilic homopolymers grafted onto spherical nanoparticles: complete embedded minimal surfaces and a machine learning algorithm for their recognition", опубликована в научном журнале Soft Matter (Q1).

🔥 Григорян Илья Валентинович.

Статья "IPECnet: ML model for predicting the area of water solubility of interpolyelectrolyte complexes", опубликована в научном журнале Physical Chemistry Chemical Physics (Q2).

🔥 Бегларян Бабкен Гагикович.

Сатья "Towards Accurate PAH IR Spectra Prediction: Handling Charge Effects with Classical and Deep Learning Models" опубликована в научном журнале Journal of Chemical Information and Modeling (Q1).

🔥 Руденко Юлия Константиновна.

Статья "Complete characterization of axisymmetric turbulent jet using background oriented schlieren and physics-informed neural network", опубликована в научном журнале Heat Transfer Research (Q2).

🔥 Чистяков Всеволод Всеволодович.

Статья "Application of Neural Networks for Path Integrals Computation in Relativistic Quantum Mechanics", опубликована в научном журнале Springer (Q4).

Скоро мы поделимся с вами историями наших победителей, в которых расскажем о процессе подготовки статьи, возникавших сложностях и эмоциях, полученных после публикации!

#исторИИ
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🌟🌟🌟 Еще раз поздравляем наших выпускников – победителей Конкурса публикаций 6-го потока обучения!

Со статьями победителей вы можете ознакомиться на нашем сайте

Напомним, что победителями стали выпускники 6-го потока обучения:

🔥 Митьковский Дмитрий Александрович.

Статья "Self-assembly of amphiphilic homopolymers grafted onto spherical nanoparticles: complete embedded minimal surfaces and a machine learning algorithm for their recognition", опубликована в научном журнале Soft Matter (Q1).

🔥 Григорян Илья Валентинович.

Статья "IPECnet: ML model for predicting the area of water solubility of interpolyelectrolyte complexes", опубликована в научном журнале Physical Chemistry Chemical Physics (Q2).

🔥 Бегларян Бабкен Гагикович.

Сатья "Towards Accurate PAH IR Spectra Prediction: Handling Charge Effects with Classical and Deep Learning Models" опубликована в научном журнале Journal of Chemical Information and Modeling (Q1).

🔥 Руденко Юлия Константиновна.

Статья "Complete characterization of axisymmetric turbulent jet using background oriented schlieren and physics-informed neural network", опубликована в научном журнале Heat Transfer Research (Q2).

🔥 Чистяков Всеволод Всеволодович.

Статья "Application of Neural Networks for Path Integrals Computation in Relativistic Quantum Mechanics", опубликована в научном журнале Springer (Q4).

Скоро мы поделимся с вами историями наших победителей, в которых расскажем о процессе подготовки статьи, возникавших сложностях и эмоциях, полученных после публикации!

#исторИИ

BY Фонд «Интеллект»








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Telegram | DID YOU KNOW?

Date: |

Again, in contrast to Facebook, Google and Twitter, Telegram's founder Pavel Durov runs his company in relative secrecy from Dubai. The regulator said it has been undertaking several campaigns to educate the investors to be vigilant while taking investment decisions based on stock tips. Stocks dropped on Friday afternoon, as gains made earlier in the day on hopes for diplomatic progress between Russia and Ukraine turned to losses. Technology stocks were hit particularly hard by higher bond yields. On February 27th, Durov posted that Channels were becoming a source of unverified information and that the company lacks the ability to check on their veracity. He urged users to be mistrustful of the things shared on Channels, and initially threatened to block the feature in the countries involved for the length of the war, saying that he didn’t want Telegram to be used to aggravate conflict or incite ethnic hatred. He did, however, walk back this plan when it became clear that they had also become a vital communications tool for Ukrainian officials and citizens to help coordinate their resistance and evacuations. Pavel Durov, a billionaire who embraces an all-black wardrobe and is often compared to the character Neo from "the Matrix," funds Telegram through his personal wealth and debt financing. And despite being one of the world's most popular tech companies, Telegram reportedly has only about 30 employees who defer to Durov for most major decisions about the platform.
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Telegram Фонд «Интеллект»
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