Xiao Zhen is from The Temple of Oufei
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Recently, the machine learning bulls have suddenly been forwarding the movement of a machine learning conference.
Either figure attention network a work by Petar Veli kovi:
Or Geometric deep learning proposer Michael Bronstein:
Everyone is paying attention to this machine learning conference, in which Bronstein also wrote a blog to call on everyone to attend.
What's going on?
It turns out that the big bulls are ready to hold an academic conference dedicated to graph & geometric machine learning.
The conference is called the Learning on Graphs Conference (LoG), which is different from academic conferences such as NeurIPS, ICML and ICLR, and the submissions received by this new conference are all related to graph & geometric machine learning.
That is to say, there are many subdivision graphs & geometric ML areas that cannot be discussed on NeurIPS, ICML and ICLR, which can be discussed on LoG, and can also get the guidance of various graph machine learning bulls.
So, what are the big bulls participating in this conference, what directions are the topics discussed, and what is the form of participation?
Let's take a look.
What kind of conference is LoG?
In fact, this conference basically "gathered" the famous graph & geometric machine learning bulls at home and abroad.
For example, Jure Leskovec, author of Graph2vec and GraphSAGE, Stefanie Jegalka, a disciple of Michael Jordan, a veteran of machine learning, and Tang Jian, who has extensive knowledge in the field of small molecule drugs, and Tang Jie, a professor at Tsinghua University, will participate in the conference.
Therefore, any topic related to graph & geometric machine learning can be put on discussion at this academic conference.
For example, application areas related to graph machine learning, including molecular discovery, physical sciences, recommendation systems, computer vision, natural language processing, etc., as well as theoretical directions such as graph neural network architecture and graph generation models, are all within the scope of discussion at this conference.
Industrial and ground-based applications such as computational chemistry, transportation networks, social networks, recommendation systems, or healthcare are also available.
Michael Bronstein believes that theoretically all subfields of graph machine learning can be discussed at this conference, so that new sparks of inspiration can be collided.
Held online for the first time, there are prizes for judging
This year is the first year of the LoG Conference, which will be held online.
Therefore, anyone can participate in this conference through the Internet and get the guidance of the big bulls.
Specific to the submission, this paper will also be conducted in the form of open review (Open Review), and the appropriate paper review is also being convened, and there is a chance to receive a reward of $1500 per person.
Judging from the time displayed on the official website, there will be opportunities to prepare papers before September.
The first LoG conference will be held in December.
Friends who have research on graph & geometric machine learning, you can consider starting to prepare & submit articles~ ~