Hello YuLun, > What do you think which model we can add besides WGAN or SGAN? Do you mean > that > add a model associate with WGAN or SGAN?
Not necessarily, but if you like you can pick another related model your choice. > what's more, do you think that it is feasible to implement both the WGAN and > SGAN separately? I think that could be interesting, maybe we can reuse some part for the other model. What do you think? I hope this is helpful. Thanks, Marcus > On 21 Mar 2017, at 05:33, YuLun Cai <[email protected]> wrote: > > Hi, Marcus > > Thanks for your reply. Sorry for forget to add the cc to mailing list in > last email. > > I think adding another model besides WGAN or SGAN would fulfill that > requirement. > > What do you think which model we can add besides WGAN or SGAN? Do you mean > that add a model associate with WGAN or SGAN? > > what's more, do you think that it is feasible to implement both the WGAN and > SGAN separately? > > Thanks > > 2017-03-19 23:32 GMT+08:00 Marcus Edel <[email protected] > <mailto:[email protected]>>: > Hello YuLun > > welcome and thanks for getting in touch! > >> I think the WGAN is wonderful, so I want to implement it too. and I'm wonder >> that is it full enough for three month's work to just implement one module >> between SGAN and WGAN? but when I want to integrate two modules I found >> there is >> not much in common between them. So I'm not sure what should I do. Can you >> give >> me some advice and guide me what should I do next? > > It is a really great idea and well written paper. Regarding if implementing a > single model SGAN or WGAN is enough work for GSoC, I don't think so, even if > you > like to implement a bunch of different test scenarios. I think adding another > model besides WGAN or SGAN would fulfill that requirement. What do you think? > > Thanks, > Marcus > >> On 19 Mar 2017, at 08:40, YuLun Cai <[email protected] >> <mailto:[email protected]>> wrote: >> >> Hello, >> I am YuLun Cai from China. I am currently in my first year of Master >> studies. I am interested in participating inGSoC 17 with mlpack in Essential >> Deep Learning Modules. >> Among the topics given on the wiki page, I am interested in implemening >> GAN modules. I have done a course in Advance Machine Learning and I've >> finished the Stanford course "CS231n: Convolutional Neural Networks for >> Visual Recognition" for self-study, which help me a lot in understand the >> deep learning. >> I've built the mlpack from source in my own machine successfully, then I >> look at the source code in the ANN module(the activation_functions, lots of >> layers and the api in ffn.hpp and rnn.hpp to learn how to build a neural >> network in mlpack) . >> I also learn to resource about GAN in the GSOC project wiki, I think the >> "Stacked Generative Adversarial Networks"[1] is interesting, which consists >> of a top-down stack of GANs and try to invert the hierarchical >> representations of a discriminative bottom-up deep network to generate >> images. >> In addition, recently the Wasserstein GAN paper[2] gets a lot of >> attention, many people think it is excellent: >> * it proposes a new GAN training algorithm that works well on the common >> GAN datasets >> * there is just a little difference between the original GAN and WGAN >> algorithm >> * its training algorithm is backed up by theory. it clarifies that the >> original GAN sometimes doesn't provide gradient to train when using KL >> divergence or JS divergence, and prove that through the Wasserstein distance >> the gradient always can be provided. >> * In the Wasserstein GAN, it can train the discriminator to convergence >> and also can improve the stability of learning, get rid of the mode collapse. >> I think the WGAN is wonderful, so I want to implement it too. and I'm >> wonder that is it full enough for three month's work to just implement one >> module between SGAN and WGAN? but when I want to integrate two modules I >> found there is not much in common between them. So I'm not sure what should >> I do. Can you give me some advice and guide me what should I do next? >> Thanks >> >> [1] https://arxiv.org/abs/1612.04357 <https://arxiv.org/abs/1612.04357> >> [2] https://arxiv.org/abs/1701.07875 >> <https://arxiv.org/abs/1701.07875>_______________________________________________ >> mlpack mailing list >> [email protected] <mailto:[email protected]> >> http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack >> <http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack> >
_______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
