Hello Aman, thanks for your interest, you are welcome to get involved.
> It would be great if you can explain more about ideas and the expected work to > be done as part of GSoC 2017. I am really looking forward to contribute to > this > project as part of GSoC. What I really like about the "Essential Deep Learning Modules" project is you can dive into some really interesting ideas and you have the chance to learn about some fundamental deep learning models from a practical perspective. Also, it is likely that people and developer will use your code or use the code that you wrote as the basis for their own models. Anyway, as stated in the project description, the focus of the project is to improve the traditional models based on recent ideas. I've linked some recent papers on the ideas pages, that revisit some of the traditional models like "Spike and slab restricted boltzmann machine" by Courville et al. or "Back to the Future: Radial Basis Function Networks Revisited" by Que and Belkin. There are a couple more references for the mentioned models, especially for GAN there are a bunch of really interesting papers that are definitely worth a look. However, the literature highly depends on the network models you like to implement over the summer. Also, to be successful at this project, you should have a good knowledge of deep learning; i.e., you should be familiar with the way deep neural networks are typically built and trained, and certainly you should be familiar with the individual components that you plan to implement. > My area of interest lies in Unsupervised learning, specifically Deep auto- > encoders as i am currently involved in the same during my master thesis work. I'd be interested to hear more about what you are doing in your thesis if you'd like to elaborate. Perhaps, implementing Deep Autoencoders is something you like to work on over the summer? In case you haven't already seen it; these pages are also helpful: http://www.mlpack.org/involved.html http://www.mlpack.org/gsoc.html I hope this is helpful; let me know if I can clarify anything. Thanks, Marcus > On 23 Feb 2017, at 19:16, Aman Gautam <[email protected]> wrote: > > Hi Marcus, > > I am a Master's student in computer science and my area of specialization > lies in Intelligent systems at TU Kaiserslautern, Germany. I am interested in > doing Essential Deep Learning Modules project as mentioned on this page: > https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas > > My area of interest lies in Unsupervised learning, specifically Deep > auto-encoders as i am currently involved in the same during my master thesis > work. As part of GSoC2017 I am interseted in working with Restricted > Boltzmann Machines (RBM) and also Generative Adversarial Networks (GAN) if > time allows. > > It would be great if you can explain more about ideas and the expected work > to be done as part of GSoC 2017. I am really looking forward to contribute to > this project as part of GSoC. > > Thanks & Regards, > Aman Gautam _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
