Deep Learning技術：押さえておくべき6つの動向(2020/08)

2020年8月現在のDeep Learningの動向から、注目しておくべきマクロな動向を6つご紹介します。

1. 継続する急速な性能向上
2. ネットワーク設計の自動化とAutoML
3. タスクの高度化と応用範囲の拡大
4. モデルのEnd-to-end化
5. モデルの大規模・高性能化
6. モデルの汎用化

DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, Yiming Yang
https://arxiv.org/abs/1806.09055

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
Han Cai, Ligeng Zhu, Song Han
https://arxiv.org/abs/1812.00332

Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros
https://arxiv.org/abs/1611.07004

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Andrew Tao, Jan Kautz, Bryan Catanzaro
https://arxiv.org/abs/1711.11585

Semantic Image Synthesis with Spatially-Adaptive Normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang, Jun-Yan Zhu
https://arxiv.org/abs/1903.07291

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros
https://arxiv.org/abs/1703.10593

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Alec Radford, Luke Metz, Soumith Chintala
https://arxiv.org/abs/1511.06434

Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras, Timo Aila, Samuli Laine, Jaakko Lehtinen
https://arxiv.org/abs/1710.10196

Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock, Jeff Donahue, Karen Simonyan
https://arxiv.org/abs/1809.11096

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, Dimitris Metaxas
https://arxiv.org/abs/1612.03242

Exploring the Limits of Weakly Supervised Pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, Laurens van der Maaten
https://arxiv.org/abs/1805.00932

Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei
https://arxiv.org/abs/2005.14165

Deep Learning入門：Transfer Learning（転移学習）
https://www.youtube.com/watch?v=sEYNDW9KSqc

再生リスト「Deep Learning入門」
https://www.youtube.com/playlist?list=PLg1wtJlhfh23pjdFv4p8kOBYyTRvzseZ3

再生リスト「Neural Network Console チュートリアル（クラウド版）」
https://www.youtube.com/playlist?index=1&playnext=1&list=PLg1wtJlhfh227oiXbVJOwXCuCoKo3dOU9

再生リスト「Neural Network Console チュートリアル（Windows版）」
https://www.youtube.com/playlist?index=1&playnext=1&list=PLg1wtJlhfh227oiXbVJOwXCuCoKo3dOU9

再生リスト「実践Deep Learning」
https://www.youtube.com/playlist?list=PLg1wtJlhfh20zNXqPYhQXU6-m5SoN-4Eu

再生リスト「Deep Learning 精度向上テクニック」
https://www.youtube.com/playlist?list=PLg1wtJlhfh216rnmSv_oEDuchRjgUqxBi

Neural Network Console
https://dl.sony.com/ja/

Neural Network Libraries
https://nnabla.org/ja/

Prediction One
https://predictionone.sony.biz/

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