Hello Rajiv, thanks again for the contributions. Implementing Graph Neural Networks is quite a challenge especially timewise but if you are up for that; we should make sure the timeline is reasonable including the milestones. Everything needs to be tests and stable at the end of the summer which often takes a lot of time, but as I said if you are up for the challenge this could be an interesting project for sure.
Let us know what you think. Thanks, Marcus > On 28. Feb 2019, at 19:14, Rajiv Vaidyanathan <[email protected]> > wrote: > > Dear Marcus, Mikhail and Shikhar, > > I am N Rajiv Vaidyanathan and I'm interested in the topic "Essential Deep > Learning Modules" in GSoC 19. > > Over the past month, I'm trying to get an understanding of the MLPack > codebase by making contributions. As of now, I have implemented SPSA > optimiser, Dice Loss function and currently working on Dense blocks. > > I recently read a paper on Graph Neural Networks and found it to be > fascinating as it works very well on non-Euclidian spaces such as social > networks and 3D images. I am interested in working on implementing this > network along with tests and documentation. I'm also interested in improving > the overall documentation of ann. > > Please let me know what you think :) > > Thanks and regards, > Rajiv > ᐧ > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
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