F
François Chollet
Researcher at Google
Publications - 22
Citations - 17379
François Chollet is an academic researcher from Google. The author has contributed to research in topics: Deep learning & Convolutional neural network. The author has an hindex of 17, co-authored 22 publications receiving 11909 citations.
Papers
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Proceedings ArticleDOI
Xception: Deep Learning with Depthwise Separable Convolutions
TL;DR: This work proposes a novel deep convolutional neural network architecture inspired by Inception, where Inception modules have been replaced with depthwise separable convolutions, and shows that this architecture, dubbed Xception, slightly outperforms Inception V3 on the ImageNet dataset, and significantly outperforms it on a larger image classification dataset.
Posted Content
Xception: Deep Learning with Depthwise Separable Convolutions
TL;DR: Xception as mentioned in this paper proposes a novel deep convolutional neural network architecture inspired by Inception, where Inception modules have been replaced with depthwise separable convolutions, which can be interpreted as an Inception module with a maximally large number of towers.
Book
Deep Learning with Python
TL;DR: Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library and builds your understanding through intuitive explanations and practical examples to apply deep learning in your own projects.
Proceedings Article
Tensor2Tensor for Neural Machine Translation
Ashish Vaswani,Samy Bengio,Eugene Brevdo,François Chollet,Aidan N. Gomez,Stephan Gouws,Llion Jones,Łukasz Kaiser,Nal Kalchbrenner,Niki Parmar,Ryan Sepassi,Noam Shazeer,Jakob Uszkoreit +12 more
TL;DR: Tensor2Tensor as mentioned in this paper is a library for deep learning models that is well-suited for neural machine translation and includes the reference implementation of the state-of-the-art Transformer model.