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DETRtime, a framework for time-series segmentation

License: MIT License

Python 99.33% Shell 0.67%
attention-mechanism convolutional-neural-networks deep-learning eeg icml-2022 time-series transformer-models

detrtime's Introduction

  • ๐Ÿ‘‹ Hi, Iโ€™m Lukas Wolf. I'm Co-founder of Sonia, an AI mental health therapist
  • ๐Ÿ”ฌ Here you find mostly work from my research in Machine Learning at MIT and ETH
  • ๐Ÿ‘€ Iโ€™m interested in Artificial Intelligence applications (Psychology, Cognitive Science and Language)
  • ๐ŸŒฑ Iโ€™m working with Hydra, PyTorch, PyTorch Lightning, and other Python/ML frameworks.
  • ๐Ÿ“ซ You can reach me on LinkedIn and X

detrtime's People

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detrtime's Issues

Discrepancy in Reproduced Results (Zuco Dataset)

Hi Lukas,

Thank you for the valuable work and for making the code and datasets publicly available. Your research is very innovative and inspiring!

I recently went through your paper DETRtime and tried to reproduce the results using the code from this repository and the provided Zuco dataset. While I followed the steps as described in the README and the paper, the validation results I obtained were notably different from those reported in the paper.

Hyperparameter setup follows the table 6 in the paper appendix:
image

Obtained results for zuco:

  1. Below are the f1 scores for each class (0, 1, 2), orange for training, blue for validation.
image
  1. Below are the weighted average f1 scores and macro average f1 scores, respectively. Orange for training, blue for validation.
image

Reported result for zuco in the paper:
image

I'm reaching out to see if there might be any additional steps, configurations, or updates that I might have missed. I'm eager to understand the potential reasons for this discrepancy. Any insights or suggestions would be highly appreciated.

Thanks.
Yicen

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