Заметки по Deep Learning ШАД.
Evgenii (Eugene) Golikov
Neural Networks and Deep Learning lab. Moscow Institute of Physics and Technology Moscow, Russia golikov.ea@mipt.ru
December 11, 2020
These are the notes for the lectures that I was giving during Fall 2020 at the Moscow Institute of Physics and Tech- nology (MIPT) and at the Yandex School of Data Analysis (YSDA). The notes cover some aspects of initialization, loss landscape, generalization, and a neural tangent kernel theory. While many other topics (e.g. expressivity, a mean-field theory, a double descent phenomenon) are missing in the current version, we plan to add them in future revisions.
Изучение методов оценки физико-механических характеристик конструкционных материалов:
- Физические свойства
- Удельные характеристики
- Гидрофизические свойства
- Прочность и долговечность конструкции
- Теплофизические свойства
Таблицы.
Файл предназначен для учебных целей. В лекции описаны механизмы взаимодействия излучений с веществом, также дается понятие радиоактивности и сильного взаимодействия:
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Notes on Deep Learning Theory Заметки ШАД (англ.)
Заметки по Deep Learning ШАД. Evgenii (Eugene) Golikov Neural Networks and Deep Learning lab. Moscow Institute of Physics and Technology Moscow, Russia golikov.ea@mipt.ru December 11, 2020 These are the notes for the lectures that I was giving during Fall 2020 at the Moscow Institute of Physics and Tech- nology (MIPT) and at the Yandex School of Data Analysis (YSDA). The notes cover some aspects of initialization, loss landscape, generalization, and a neural tangent kernel theory. While many other topics (e.g. expressivity, a mean-field theory, a double descent phenomenon) are missing in the current version, we plan to add them in future revisions.
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