Learning and Predicting Chaos using LSTM RNNs

Independent study and research on modeling chaotic systems using Long Short Term Memory recurrent neural networks. Done with the guidance and support of Dr. Tom Gibbons at The College of St. Scholastica, Duluth, MN.

Presented at the 2018 Midwest Instruction and Computing Symposium. See details in our poster or read this paper

Software

• Jupyter Notebook: Keras backend, iPyWidgets, IPython, Numpy, Scipy, and MatPlotLib libraries.

Citing our work

If you find this project useful and you use it in any of your work, please cite it as follows:

@inproceedings{madondo2018learning,
  title={Learning and modeling chaos using lstm recurrent neural networks},
  author={Madondo, Malvern and Gibbons, Thomas},
  year = {2018}
}