Загрузка страницы
Все видеоНовые видеоПопулярные видеоКатегории видео

Memory-Efficient aggregations [Advanced PyTorch Geometric Tutorial 6]

In this tutorial, we discuss how the new version of PyTorch Geometric leverages sparse matrices to improve the computational efficiency and memory footprint of message passing. We review some background on the representation of sparse matrices, have a look at the SparseTensor class from PyTorch Sparse, and analyze the new message_and_aggregate method in PyG.

Видео Memory-Efficient aggregations [Advanced PyTorch Geometric Tutorial 6] канала Antonio Longa
Показать
Комментарии отсутствуют
Введите заголовок:

Введите адрес ссылки:

Введите адрес видео с YouTube:

Зарегистрируйтесь или войдите с
Информация о видео
18 декабря 2021 г. 22:57:53
00:35:51
Antonio Longa
Правообладателям
Жалоба
Комментарии
Другие видео канала
Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and OpportunitiesGraph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and OpportunitiesTalk at Cambridge University - Neighbourhood matching creates realistic surrogate temporal networksTalk at Cambridge University - Neighbourhood matching creates realistic surrogate temporal networksComplex Networks 2021 - Madrid - POSTER session - ETMM: Egocentric temporal motifs minerComplex Networks 2021 - Madrid - POSTER session - ETMM: Egocentric temporal motifs minerAdvanced mini-batching [Advanced PyTorch Geometric Tutorial 5]Advanced mini-batching [Advanced PyTorch Geometric Tutorial 5]Heterogeneous graph learning [Advanced PyTorch Geometric Tutorial 4]Heterogeneous graph learning [Advanced PyTorch Geometric Tutorial 4]Egocentric Temporal Motifs Miner (ETMM) [Paper explanation and code usage]Egocentric Temporal Motifs Miner (ETMM) [Paper explanation and code usage]Price Graphs [Advanced PyTorch Geometric Tutorial 3]Price Graphs [Advanced PyTorch Geometric Tutorial 3]GraphGym and PyG [Advanced PyTorch Geometric Tutorial 2]GraphGym and PyG [Advanced PyTorch Geometric Tutorial 2]Open Graph Benchmark and PyG [Advanced PyTorch Geometric Tutorial 1]Open Graph Benchmark and PyG [Advanced PyTorch Geometric Tutorial 1]Pytorch Geometric tutorial: Graph pooling DIFFPOOLPytorch Geometric tutorial: Graph pooling DIFFPOOLPytorch Geometric tutorial: Special Guest: Sergei IvanovPytorch Geometric tutorial: Special Guest: Sergei IvanovPytorch Geometric tutorial: Special Guest: Matthias FeyPytorch Geometric tutorial: Special Guest: Matthias FeyPytorch Geometric tutorial: Data handling in PyTorch Geometric (Part 2)Pytorch Geometric tutorial: Data handling in PyTorch Geometric (Part 2)Pytorch Geometric tutorial: Data handling in PyTorch Geometric (Part 1)Pytorch Geometric tutorial: Data handling in PyTorch Geometric (Part 1)Pytorch Geometric tutorial: Metapath2VecPytorch Geometric tutorial: Metapath2VecPytorch Geometric tutorial: Edge analysisPytorch Geometric tutorial: Edge analysisPytorch Geometric tutorial: DeepWalk and Node2Vec (Practice)Pytorch Geometric tutorial: DeepWalk and Node2Vec (Practice)Pytorch Geometric tutorial: DeepWalk and Node2Vec (Theory)Pytorch Geometric tutorial: DeepWalk and Node2Vec (Theory)Pytorch Geometric tutorial: Recurrent Graph Neural NetworksPytorch Geometric tutorial: Recurrent Graph Neural NetworksPyTorch Geometric tutorial: Graph GenerationPyTorch Geometric tutorial: Graph Generation
Статистика портала
Яндекс.Метрика
© 2008-2024 «Информационно-развлекательный портал города Верхняя Салда»
| Карта портала | Реклама | Контакты | Сообщить об ошибке | Соглашения
salda.ws salda.ws@mail.ru
Сейчас на сайте: 512 Статистика портала