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Associative Transformer

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The code repository for "Associative Transformer Is A Sparse Representation Learner" paper (NeurIPS23 workshop) in PyTorch.

Associative Transformer (AiT) enhances ViT and sparse attention-based models such as the Coordination and Perceiver, building upon neuroscience studies of associative memory.

Training

AiT on CIFAR10

  python ait.py

Customized Settings (refer to the paper)

  python ait.py --warmup_t $warmup_t --beta $beta --pattern_size $pattern_size --memory_dim $memory_dim --bottleneck $bottleneck --dataset $dataset --epochs $epochs --batch_size $batch_size --patch_size $patch_size --model_size $model_size

Citation

If this repository is helpful for your research or you want to refer the provided results in this work, you could cite the work using the following BibTeX entry:

@article{sun2023associative,
  author = {Yuwei Sun, Hideya Ochiai, Zhirong Wu, Stephen Lin, Ryota Kanai},
  title = {Associative Transformer is a Sparse Representation Learner},
  journal = {arXiv preprint:2309.12862},
  year = {2023}
}

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