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mlverse
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tft
R implementation of Temporal Fusion Transformers
https://mlverse.github.io/tft/
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luz::lr_finder() Segmentation fault
#43
agorelick
opened
1 week ago
2
Cannot find the electricity dataset
#42
binh0206
opened
1 year ago
6
Predicting on data with gaps in date variable
#41
vidarvr
opened
1 year ago
1
Error if spec_covariate_known is not supplied
#40
vidarsumo
closed
1 year ago
2
Error in `verify_new_data()`
#39
Sanaxen
opened
2 years ago
6
Crashes when running on GPU (cuda11.3)
#38
Sanaxen
closed
2 years ago
2
Use TFT with GPU
#37
vidarsumo
opened
2 years ago
3
Minimum number of observation in relation to lookback
#36
vidarsumo
closed
2 years ago
1
index and key are not present when using predict
#35
vidarsumo
opened
2 years ago
7
Subsample
#34
dfalbel
closed
2 years ago
0
Decouple data preparation from model definition
#33
dfalbel
closed
2 years ago
0
Support valid data
#32
dfalbel
closed
2 years ago
0
Pass validation data to `tft`.
#31
dfalbel
closed
2 years ago
1
It should be easy to refit models
#30
dfalbel
opened
2 years ago
0
Refactor `predict`
#29
dfalbel
closed
2 years ago
0
Allow serialization of the models.
#28
dfalbel
closed
2 years ago
0
`time_series_dataset` bug when skip is set
#27
dfalbel
closed
2 years ago
0
Normalization constants are not correctly applied to the predictions when `mode="full"`
#26
dfalbel
closed
2 years ago
0
Make sure `new_data` is complete when using the `full` mode
#25
dfalbel
closed
2 years ago
0
Start adding full prediction mode.
#24
dfalbel
closed
2 years ago
0
Predict with a fixed model for multiple timesteps
#23
dfalbel
closed
2 years ago
0
Improve error message when lookback is too large for the provided data
#22
dfalbel
closed
2 years ago
0
Major refactoring
#21
dfalbel
closed
2 years ago
0
Feedback on the API
#20
dfalbel
opened
2 years ago
1
Feature/add recipe assertions
#19
cregouby
closed
2 years ago
0
Error in torch_tensor_cpp(data, dtype, device, requires_grad, pin_memory) : object 'device' not found
#18
3SMMZRjWgS
closed
2 years ago
2
Data structure
#17
dfalbel
closed
2 years ago
1
Figure out if we can reproduce benchmarks
#16
dfalbel
opened
2 years ago
0
Feature/importance plot
#15
cregouby
closed
2 years ago
0
Using predict with tft_fit model
#14
Boeinco
closed
2 years ago
3
Not able to download
#13
shanepiesik
closed
2 years ago
1
Fix Mixed tensor devices in running README.md
#12
cregouby
closed
3 years ago
0
Feature/add recipe assertions
#11
cregouby
closed
2 years ago
0
add workflow for codecov
#10
cregouby
closed
2 years ago
0
Mixed tensor devices in running README.md example
#9
cregouby
closed
3 years ago
0
Roadmap to integrate with {fable} or {modeltime}
#8
cregouby
opened
3 years ago
3
Figure out exactly what API we want.
#7
cregouby
opened
3 years ago
0
Add a simple example that can be easily compared with a common approach like ARIMA or ETS.
#6
cregouby
opened
3 years ago
0
make predict.tft() compatible with yardstick::metricset() usage
#5
cregouby
opened
3 years ago
0
add consistency check in the dataset submitted
#4
cregouby
closed
2 years ago
0
add consistency check in recipes role attribution
#3
cregouby
closed
2 years ago
0
implement the tft-vectorisation speedup trick with sqash_batch_dimension
#2
cregouby
opened
3 years ago
0
add working tft_fit()
#1
cregouby
closed
3 years ago
11