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请参考文章附录E中的相关讨论:
To ensure a fair comparison between models, we conducted experiments using unified parameters and reported results in the main text, including aligning all the input lengths, batch sizes, and training epochs in all experiments.
In addition, considering that the reported results in different papers are mostly obtained through hyperparameter search, we provide the experiment results with the full version of the parameter search.
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Related Issues (20)
- 运行脚本出现以下错误,请问该怎么处理 HOT 3
- 周期趋势的分解 HOT 2
- GELU hard coded HOT 1
- 运行short_term_forecast出现如下报错 HOT 1
- 请问这两行代码的作用是什么? HOT 8
- 关于lab_len HOT 1
- Perhaps the logic errors in the code HOT 1
- 设置 args.features = 'MS'时程序错误 HOT 3
- 在短期预测读取m4数据 HOT 8
- B, T, N = x.size()出错 HOT 4
- The “freeze_support()” line can be omitted if the program is not going to be frozen to produce an executable. HOT 3
- Forecastability的计算 HOT 1
- normalize HOT 1
- seq_len为奇数的时候__multi_scale_process_inputs有问题 HOT 1
- loss exploding after some iterations HOT 1
- no one scripts can be run HOT 1
- 这个问题是怎么造成的呢 HOT 1
- Test Loss: 41927.7059582 ??? With default hyper-parameters HOT 5
- Why does it look terrible in results? (Weather dataset) HOT 1
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