Заметки по Deep Learning ШАД.
Evgenii (Eugene) Golikov
Neural Networks and Deep Learning lab. Moscow Institute of Physics and Technology Moscow, Russia [email protected]
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:
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 [email protected] 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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