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 convolutional neural networks are becoming less useful. In this paper, we introduce Chainer, a Python based, standalone open source framework for deep learning models. Chainer provides a flexible, intuitive, and high performance means of implementing a full range of deep learning models, including state-of-the-art models such as recurrent neural networks and variational autoencoders.

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Code (1)

chainer/chainer

Tasks

ClusteringDeep LearningDimensionality Reduction General Classification

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)

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

HypoChainer: A Collaborative System Combining LLMs and Knowledge Graphs for Hypothesis-Driven Scientific Discovery

2025-07-23 · Haoran Jiang, Shaohan Shi, Yunjie Yao, Chang Jiang 외 arxiv

Modern scientific discovery faces growing challenges in integrating vast and heterogeneous knowledge critical to breakthroughs in biomedicine and drug development. Traditional hypothesis-driven research, though effective…

Dimensionality Reduction Knowledge Graphs

Chainer: A Deep Learning Framework for Accelerating the Research Cycle

2019-08-01 · Seiya Tokui, Ryosuke Okuta, Takuya Akiba, Yusuke Niitani 외

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 …

Deep Learning

ChainerMN: Scalable Distributed Deep Learning Framework

2017-10-31 · Takuya Akiba, Keisuke Fukuda, Shuji Suzuki

One of the keys for deep learning to have made a breakthrough in various fields was to utilize high computing powers centering around GPUs. Enabling the use of further computing abilities by distributed processing is ess…