DLPaper2Code

Q1: How often do you read a research paper discussing a deep learning algorithm ?

Q2: Assuming that you come across a relevant research paper, how much time does it take for you to understand the research paper?

Q3: Assuming that you are successful in understanding the paper, how much time does it take for you to implement the paper in a single library (say Tensorflow) ?

Q4: Assuming that you implement the research paper in a single library, how much time does it take for you to implement the research paper in other libraries (say Keras, Caffe, PyTorch etc) ?

Q5: Assuming that you implemented the research paper in multiple libraries, how much time does it take for you to debug the implementation and make it bug free?

Answer: Assuming that you have read this post till here, what if I say that the time taken for you to read the above 5 questions is now more than the time taken for you to perform them!

This is our goal in our research paper published in the AAAI Conference on Artificial Intelligence (AAAI-18) called “DLPaper2Code: Auto-generation of Code from Deep Learning Research Papers”

Please find the poster here, that we presented in AAAI-2018 conference.

Please note that this feature is an initial proof of concept, and is not yet available as a system for open consumption.

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IBM Deep Learning IDE (DL-IDE)

Along with this, we have built our easy-to-use, intuitive IDE for deep learning called -IBM Deep Learning IDE (DL-IDE). Play around with it - lots of cool features secretly built into it and lot more coming!

Watch the demo video here for the existing features and features to come -

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AAAI 2018 Presence

I am presenting four papers (1 AAAI, 1 IAAI, 2 Technical Demo) in #AAAI2018, New Orleans (AAAI)

For more information on the papers, visit IBM Research AI Blog

If you are around, do reach out to me at anussank@in.ibm.com or tweet to me @goodboyanush