MERA_Image_Classification Code Contributor: Fanjie Kong Finished Work: Implemented 2D MERA model using PyTorch and TensorFlow. TensorFlow version is more time-efficient. Tested our 2D MERA model on MNIST, NeedleMNIST(64x64, 128x128) and LIDC dataset. MNIST NeedleMNIST(64x64) NeedleMNIST(128x128) LIDC CNN 0.983 0.760 0.739 0.780 Tensor-NN 0.985 0.740 0.727 0.860 2D MERA 0.903 0.784 0.714 0.760 Summarized our work into a paper submitted to QTNML 2020 Description: PyTorch codes: Basic Pytorch dependency Tested on Pytorch 1.3, Python 3.6 Unzip the data and point the path to --data_path How to run tests: python train.py --data_path data_location TensorFlow code: TensorFlow 2.1.0 and TensorNetwork Experiments are performed on Jupyter Notebook MERA_MNIST.ipynb Thanks to the following repositories: https://github.com/raghavian/loTeNet_pytorch