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Orthogonal Tensor Trains (OTT)

Various implementations for the experiments in the paper below. Simulations and moving MNIST include Tensorflow implementations, while Hollywood2 and Neuroimaging experiments were conducted using PyTorch.

Some details (re: neuroimaging data) have been omitted.

Dependencies

Works with Tensorflow 1.12 and 1.14. Pytorch 1.0.1 was used for neuroimaging experiments. Keras 2.1.2 (with TF 1.12) was used for Hollywood2 experiments.

Reference and Links

    "Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains"
    Ronak Mehta, Rudrasis Chakraborty, Yunyang Xiong, Vikas Singh
    In International Conference on Computer Vision 2019 (ICCV-2019).

A link to the paper will be updated as it is available!

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