ICLR 2017: Conference Report & Coming ICML

miyato

2017-07-21 11:20:57

I am Takeru Miyato, a researcher at Preferred Networks (PFN), and I participated in  ICLR 2017 (4/24-4/26), which is the biggest conference on deep learning research.

Let me give you a brief overview of the event. ICLR has been held since 2013 and this was the fifth ICLR. The main features of ICLR are:

  • Focus on deep learning and its application. Most of the papers focus on neural networks.
  • Adaptation of open review system. Everyone can join the review process. To be precise, everyone can see the all of the reviews and rebuttals and also can comment, ask questions, and post his or her reviews as public reviews. In addition, authors can update their paper anytime from the feedback until the end of the discussion phase.

As far as I know, there is no other conference exposing the all of the reviews and rebuttals to the public, which I think is interesting / helpful to the people who write or review research papers. Also, some people analyzed the submissions and reviews, and they posted articles with interesting results. Here are some links to a pair of interesting ones:

more »

IV 2017: Conference Report

maruyama

2017-07-13 10:56:42

Writers: Tommi Kerola, Shintarou Okada, Shirou Maruyama

Preferred Networks (PFN) was present at the IEEE IV 2017 conference in Redondo Beach, CA, US, one of the flagship conferences for discussing research and applications for intelligent vehicles, including techniques for autonomous driving. Autonomous driving is one of the fields of main importance for PFN, which is why three of our members attended the conference in order to learn more about the latest research, and to connect with people from both academia and the industry. In this blog post, we will briefly summarize trends from this conference, focusing mainly on perception and motion planning.

 

more »

Chainer-GAN-lib Release

matsumoto

2017-07-11 10:30:40

We released chainer-GAN-lib: the collection of Chainer implementation of recent GAN variants. This library is targeted to those who think “the progress of GAN is too fast and hard to follow”, “Experiments in GAN articles can not be reproduced at all”, “How can I implement the gradient penalty with Chainer?”

https://github.com/pfnet-research/chainer-gan-lib

more »

Preferred Networks during ICRA: Conference Report

jethrotan

2017-07-03 11:30:12

Preferred Networks (PFN) was present at IEEE ICRA 2017, world’s biggest annual robotics conference, as exhibitor, invited speaker, and silver grade sponsor. A total of 3221 people attended the conference this year, which is more than double of last year’s attendance. As robotics is one of the fields of major importance within PFN, we have sent as much as ten of our members to attend ICRA.

more »