Implementation of Bidirectional Recurrent Independent Mechanisms (Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules)

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Deep LearningBRIMs
Overview

BRIMs

Bidirectional Recurrent Independent Mechanisms

Implementation of the paper Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules

@article{mittal2020learning,
  title={Learning to combine top-down and bottom-up signals in recurrent neural networks with attention over modules},
  author={Mittal, Sarthak and Lamb, Alex and Goyal, Anirudh and Voleti, Vikram and Shanahan, Murray and Lajoie, Guillaume and Mozer, Michael and Bengio, Yoshua},
  journal={arXiv preprint arXiv:2006.16981},
  year={2020}
}

MNIST Experiments

To run MNIST Experiments, please use the following command

python train_mnist.py --emsize 300 --nlayers 2 --cuda --cudnn --algo blocks --num_blocks 6 3 --topk 4 2 --nhid 300 300 --use_inactive

CIFAR10 Experiments

To run CIFAR10 Experiments, please use the following command

python train_cifar.py --emsize 300 --nlayers 2 --cuda --cudnn --algo blocks --num_blocks 6 6 --topk 4 4 --nhid 300 300 --use_inactive

Owner
Sarthak Mittal
Graduate Student Department of Mathematics Universite de Montreal / MILA
Sarthak Mittal
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