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Chainer: A Deep Learning Framework for Accelerating the Research Cycle

2019-08-01 · Seiya Tokui, Ryosuke Okuta, Takuya Akiba, Yusuke Niitani, Toru Ogawa, Shunta Saito, Shuji Suzuki, Kota Uenishi, Brian Vogel, Hiroyuki Yamazaki Vincent

Software frameworks for neural networks play a key role in the development and application of deep learning methods. In this paper, we introduce the Chainer framework, which intends to provide a flexible, intuitive, and high performance means of implementing the full range of deep learning models needed by researchers and practitioners. Chainer provides acceleration using Graphics Processing Units with a familiar NumPy-like API through CuPy, supports general and dynamic models in Python through Define-by-Run, and also provides add-on packages for state-of-the-art computer vision models as well as distributed training.

📄 PDF Abstract BibTeX arXiv:1908.00213

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Deep Learning

ChainerRL: A Deep Reinforcement Learning Library

2019-12-09 · Yasuhiro Fujita, Prabhat Nagarajan, Toshiki Kataoka, Takahiro Ishikawa

In this paper, we introduce ChainerRL, an open-source deep reinforcement learning (DRL) library built using Python and the Chainer deep learning framework. ChainerRL implements a comprehensive set of DRL algorithms and t…

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

ChainerCV: a Library for Deep Learning in Computer Vision

2017-08-28 · Yusuke Niitani, Toru Ogawa, Shunta Saito, Masaki Saito

Despite significant progress of deep learning in the field of computer vision, there has not been a software library that covers these methods in a unifying manner. We introduce ChainerCV, a software library that is inte…

Deep Learning object-detection Object Detection Semantic Segmentation

Chainer: a Next-Generation Open Source Framework for Deep Learning

2015-01-01 · NIPS 2015 1 · Seiya Tokui, Kenta Oono, Shohei Hido, Justin Clayton

Software frameworks for neural networks play key roles in the development and application of deep learning methods. However, as new types of deep learning models are developed, existing frameworks designed for convolutio…

Clustering Deep Learning Dimensionality Reduction General Classification

Kyoto-NMT: a Neural Machine Translation implementation in Chainer

2016-12-01 · COLING 2016 12 · Fabien Cromi{\`e}res

We present Kyoto-NMT, an open-source implementation of the Neural Machine Translation paradigm. This implementation is done in Python and Chainer, an easy-to-use Deep Learning Framework.

Deep Learning Language Modeling Language Modelling Machine Translation+2

LB-CNN: An Open Source Framework for Fast Training of Light Binary Convolutional Neural Networks using Chainer and Cupy

2021-06-25 · Radu Dogaru, Ioana Dogaru

Light binary convolutional neural networks (LB-CNN) are particularly useful when implemented in low-energy computing platforms as required in many industrial applications. Herein, a framework for optimizing compact LB-CN…

Face Recognition