A lot of people like Torch. I haven't looked at pylearn2 in a while, but that might be good too. Then there are a few researcher libraries with limited documentation. Nitish Srivastava has his DeepNet library and George Dahl has gdbn and there are certainly a few others too. Who knows, maybe people will start contributing documentation.
I would probably recommend Torch at this point. The incentives don't exist for the experts to make really good open source projects and spend all the time required maintaining them and helping people with them.
That's fine. I do this full time. Despite it being new, I'm coming at it from a stand point of providing a platform for newer users and apps around it. You would be surprised the demand for industry.
You're right about this which is why I started a company around it.
I've already talked with andrew ng and yoshua bengio. My incentives are different from there's, however, I do have their blessings to continue doing this.
I walked in to this expecting skeptics. That being said, I love deep learning as a field and will be implementing every possible neural net I can. Since my incentives are different, I can explore the different use cases with customers and help further the field in different directions that might not make sense for say baidu, facebook ,or google.
I would probably recommend Torch at this point. The incentives don't exist for the experts to make really good open source projects and spend all the time required maintaining them and helping people with them.