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August 27 — September 1, , Moscow, Russia. At Deep Bayes summer school, we will discuss how Bayesian Methods can be combined with Deep Learning and lead to better results in machine learning applications. Recent research has proven that the use of Bayesian approach can be beneficial in various ways. School participants will learn methods and techniques that are crucial for understanding current research in machine learning.

They will also have hands-on experience with using probabilistic modeling to build neural generative and discriminative models, learn modern stochastic optimization methods and regularization techniques for neural networks, and master the ways to reason about the uncertainty about the weight of the neural networks and their predictions. Lectures will be followed by practical sessions. Our summer school is intended for: Undergraduate students preferably those who completed at least 2 years of study and graduate students with strong mathematical background and decent knowledge of machine learning including deep learning Researchers and industry professionals working in machine learning or related areas, willing to expand their knowledge and skills.

Our goal is to show that using the Bayesian approach in deep learning models can expand the range of their applicability and improve their performance. Although there are many different problem settings in machine learning, probabilistic inference for Bayesian networks can be performed in a similar way for most of them. Do you want to learn more about these methods?

Come to our summer school! Unfortunately, we had to cancel this year's school due to the global pandemic. Check back next year and be sure to watch previous year's videos. Today, the Bayesian Methods Research group is one of the leading machine learning research groups in Russia. Members of the group have developed a range of university courses in Bayesian Methods, Deep Learning, Optimization and Probabilistic Graphical Models and have substantial teaching experience.

The working language of the school is English. All the lectures and practical sessions will be held in English, so the participants will need sufficient proficiency in technical English. The fee is rubles approx. No, candidates will have to complete the application form.

The participants will be selected on a competitive basis. Only approved candidates will be asked to proceed with paying the fee. The selection process is necessary because we have a limited number of spots available, and we also want to make sure that our participants have a suitable background to understand the material and have a useful experience at Deep Bayes School. Candidates fill an application form, write a short essay paper review and complete a few small assignments to demonstrate their knowledge of machine learning and programming skills.

The selection committee will carefully review all the applications and will proceed with the strongest candidates based on their technical skills and motivation.

Last year we received about applications for slots however, for this year the number of available slots may be different. Unfortunately, no. Our summer school is intended for candidates who have strong knowledge of machine learning and are familiar with neural networks.

Such level of participants enables us to delve into to technical details and quickly proceed to advanced topics while being confident that the material is accessible for everyone. For learning machine learning fundamentals, we encourage you to check out numerous resources available on the web.

You will learn modern techniques in deep learning and discover benefits of Bayesian approach for neural networks. Topics discussed during the School will help you understand modern research papers.

And, of course, the School provides an excellent opportunity to meet like-minded people and form new professional connections with speakers, tutors and fellow school participants. Yes, if you get selected. We will provide a limited number of travel grants. The amount of the travel grant is fixed no matter from which country the participant comes. Travel grant can be spent to cover a trip to and from Moscow and accommodation for the time of the summer school.

Yes, we will provide visa invitation letters for those selected participants who need Russian visa. If you have any further questions about our summer school, feel free to send us an email to info deepbayes. Toggle navigation. Organized by. Participation prerequisites. Strong knowledge of machine learning, familiarity with deep learning and basics of bayesian machine learning.

Mathematics: proficiency in linear algebra and probability theory is highly desirable. English will be the language of Deep Bayes summer school, so participants are expected to be comfortable with technical English. What will I learn at the Deep Bayes school? Why are Bayesian methods useful in machine learning and everyday life? What is randomness, indeed? Latent Variable Models. How to train a model able to discover patterns unknown before training? Scalable probabilistic models.

Why can it be useful to turn a probabilistic inference problem into an optimization problem? How to train an infinite ensemble of neural networks using the same amount of memory? Stochastic optimization. How to optimize a function faster than computing its value at one point? How to apply well-established probabilistic modeling tools such as MCMC and Gaussian processes to modern large-scale problems? Andrey Malinin Yandex Research. Evgeny Burnaev Associate Professor, Skoltech.

Yermek Kapushev PhD student, Skoltech. Dmitry Vetrov Head of the School. Nadezhda Chirkova Organizer. Ekaterina Lobacheva Organizer. Ekaterina Volzhenina Organizer. Darya Voronkova Organization Manager. What is the language of the school? What is the participation fee? If I pay the fee, does it automatically mean I can participate? What is the selection process like? How competitive is the admission? Will meals be provided? We will provide coffee breaks and lunches. I do not know much about machine learning, but I would like to learn more.

Should I participate in Deep Bayes school? What will I get from participating in the School? I live outside Moscow.

Can I still participate? What about lectures live streaming? Will you help me to obtain Russian visa? I have more questions! Please, email us at info deepbayes.

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O. "Member" means a sworn employee of the Bureau or a supervisor of sworn employees. the Director may compel review by the Police Review Board of any RU.

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The Russian Federation is committed to achieve the goals defined by the international community in the Agenda. This work has been done as a direct continuation of the activities in the framework of the Millennium Development Goals achievement. While the concept of sustainable development was formulated and has become an integral part of the national development concept of Russia in The Russian Federation is a multinational social State with its policy centered around people, their rights and freedoms, welfare and quality of life. The implementation of those principles is consistent with sustainable human development realized through public and private initiatives aimed at the development of education and health care systems, social protection, transport, digital and energy infrastructure as well of as the economy as a whole and the environment protection.


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The main questions of meat raw material processing, improvement of technologies for meat product manufacture including functional foods, effects of meat and meat product consumption on human health are highlighted. The main tasks of the journal consist in the publication of scientific research results and theoretical and experimental studies carried out in the Russian and foreign organizations, as well as on the authors' personal initiative; bringing together different categories of researchers, university and scientific intelligentsia; to create and maintain a common space of scientific communication, bridging the gap between the publications of regional, federal and international level. The journal content areas reflect the modern state of different scientific and technical problems, the industrial implementation of scientific results and advanced home and foreign experience: such as regulation of feeding rations and keeping conditions, targeted modification selection, hybridization, operative manipulations with animals and poultry ; the study of effects of the main meat nutrients proteins, lipids , micro- and macroelements, vitamins, their compatibility and preservation during meat and poultry product manufacture on meat quality and properties. All publication costs for the Journal are covered by the V. Authors of articles published in the Journal retain the copyright of their articles and are free to reproduce and disseminate their work. All articles are licensed under a Creative Commons Attribution 4. We follow the open access policy proclaimed by the Budapest Open Access Initiative to encourage knowledge sharing across the globe. For more information please read BOAI statement.

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The program is designed for 3 years with an extension every year. Projects are carried out under the supervision of a professor.

This post is also available in: EN RU. IGT-Service provides independent comprehensive analysis of projects, focused on disclosure of objective information and presentation of current project status. During collection of information we take into account any available information, regardless of its sources of origin. Acquired information is reviewed by various individual specialists, then a summary analysis is developed. Due Diligence experts make their opinion independently from the customer. Expert findings may be presented in full with attached individual intermediate conclusions by experts, data sources , or as summary recommendations for further action. Development of GIS projects, which, according to current requirements, are to be created at the start of on-site operations, evolve and get updated along the way, is a separate activity field.

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