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Hi, I have read the paper and the FDA code. It's really a novel work with a nice perspective.
In paper I found that this work claims that using high-frequency can help the visual-textual matching, …
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Hello,
I want to forecast electricity demand. It typically has some daily and weekly seasonal pattern. Therefore, some people claim, one might use a double seasonal ARIMA approach.
I wonder, whe…
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While translating the book to the Portuguese version, we have found some problems with chunk 19: nb_reg in Time series chapter.
Line 590
observed
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I'm interested in learning how to use the operators in e2cnn/escnn to implement a function f such that f(Fea_I) = Fea_I_rot. Here, Fea_I = B(I) represents the feature of an image I after passing throu…
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Another interesting-looking paper!
https://arxiv.org/abs/2202.11214
To quote the abstract:
> FourCastNet, short for Fourier Forecasting Neural Network, is a global data-driven weather foreca…
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**Abstract**
Computers can tell us whether we’re happy, sad, angry or any of the several emotions we feel. Computers can understand what we’re saying and answer back. How does all this magic happen? …
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Extract basic features from time series data and reasonably past, possibly using some parallelization.
Jswig updated
5 years ago
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There are many types of models: physics based models, ODEs, machine learning models, deep learning, etc.
Can we analyze the model imports and how they are used to determine the type of model?
Fo…
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## 🐞Describing the bug
I tried to convert the Pytorch model with the function torch.fft.irfft, but it failed with the error below:
**ValueError: Op "complex_irfft_0" (op_type: complex_irfft) Input d…
xyu2 updated
7 months ago