-
Hi!
Thanks for an awesome and easy-to-use package!
I'm currently doing some marketing mix forecasting and was wondering, is their any way (by parameter or transform) to ensure that learned coeff…
-
It seems to me that there are some consistency and naming issues with the way wrapping and metadata attachment are done; I don't know how to address them all at once, but here is a list of current beh…
-
Dear Developers,
I currently actively use a code from your colleagues called JIDT/IDTxl, I'm sure you are familiar with it. Currently my code works well, but has prohibitively high computation time…
-
Hi Matt,
First of all, thanks for all you are doing around modeltime. It's clearly a big step forward for TimeSeries modeling.
Perhaps it is already covered but I am not able to see if in modelt…
-
Take the experiment of electricity for example, I notice that in the second window of the test set of each id in your code, it has the conditioning range with the ground truth of the values of 2014-…
-
Hi,
I was looking for motif discovery on timeseries and find this one. Seems very good, but my data has several variables, it's a multivariate time serie.
This library doesn't support that, right?…
-
I am currently checking `TimeGPT` with multivariate timeseries data and comparing it against univariate timeseries data, hoiwever there is no difference in the forecasts.
- The univariate data has …
-
# URL
- https://arxiv.org/abs/2403.19888
# Affiliations
- Ali Behrouz, N/A
- Michele Santacatterina, N/A
- Ramin Zabih, N/A
# Abstract
- Recent advances in deep learning have mainly relied on …
-
### Background
Gradient-based inference (like the HMC greta uses) can only operate on continuous parameter spaces. That means it cannot learn the values of parameters with discrete support (e.g. no…
-
### Describe the issue:
When running the [Bayesian Vector Autoregressive Models — PyMC example gallery 1](https://www.pymc.io/projects/examples/en/latest/time_series/bayesian_var_model.html) on x86…