tenghu/lstm-to-solve-the-xor-problem

OpenAI - Request for Research 2.0 (https://blog.openai.com/requests-for-research-2/) Warmup

Train an LSTM to solve the XOR problem: that is, given a sequence of bits, determine its parity. The LSTM should consume the sequence, one bit at a time, and then output the correct answer at the sequence’s end. Test the two approaches below:

1. Generate a dataset of random 100,000 binary strings of length 50. Train the LSTM; what performance do you get?

2. Generate a dataset of random 100,000 binary strings, where the length of each string is independently and randomly chosen between 1 and 50. Train the LSTM. Does it succeed? What explains the difference?

lstm-to-solve-the-xor-problem's Issues

any plans to add a license for this repo?

see also https://help.github.com/articles/adding-a-license-to-a-repository/