Democratization of Deep Learning Using DARVIZ

Authors

  • Anush Sankaran IBM Research AI
  • Naveen Panwar IBM Research AI
  • Shreya Khare IBM Research AI
  • Senthil Mani IBM Research AI
  • Akshay Sethi IIIT Delhi
  • Rahul Aralikatte IBM Research AI
  • Neelamadhav Gantayat IBM Research AI

Keywords:

Deep Learning, Research Paper Mining, DARVIZ

Abstract

With an abundance of research papers in deep learning, adoption and reproducibility of existing works becomes a challenge. To make a DL developer life easy, we propose a novel system, DARVIZ, to visually design a DL model using a drag-and-drop framework in an platform agnostic manner. The code could be automatically generated in both Caffe and Keras. DARVIZ could import (i) any existing Caffe code, or (ii) a research paper containing a DL design; extract the design, and present it in visual editor.

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Published

2018-04-29

How to Cite

Sankaran, A., Panwar, N., Khare, S., Mani, S., Sethi, A., Aralikatte, R., & Gantayat, N. (2018). Democratization of Deep Learning Using DARVIZ. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/11376