Alexander März

Meta-Forecasting by combining Global Deep Representations with Local Adaptation

2

## Description Referring to your paper [Meta-Forecasting by combining Global Deep Representations with Local Adaptation](https://arxiv.org/pdf/2111.03418.pdf), I would like to kindly ask if there is an implementation available on your repo?

Forecast Reconciliation

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## Description It would be very useful to allow for forecast reconciliation of hierarchical and/or grouped time series. This means that the sum of all forecasts that make up a...

## Summary It would be great to add **Scalable Representation Learning for Multivariate Time Series** as an additional feature input to models implemented in to Pytorch-TS. ## Potential Benefits Both...

How to use your approach for downstream forecasting tasks

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## Summary Thanks for making the code available. I really like the idea of first learning the embeddings in a self-supervised manner and then using a simpler model for forecasting....

Py-BoostLSS: An extension of Py-Boost to probabilistic modelling

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Dear Py-Boost developers, Thanks for the very interesting paper and for making the code publicly available. I am the author of [XGBoostLSS](https://github.com/StatMixedML/XGBoostLSS) and [LightGBMLSS](https://github.com/StatMixedML/LightGBMLSS) that extend the base implementations to...

Document how to make reproducible runs with GluonTS

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## Description Hello, I am working with PyTorch-models in GluonTS and trying to make results reproducible. In particular, I would like to set a global seed to ensure that the...

Support custom evaluation metrics and loss_function in R

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Problem: Support custom evaluation metrics and loss_function in R catboost version: >= v0.15.2 Operating System: Windows / Linux / Mac CPU: # GPU: Dear Catboost developer team, it would really...

Hi, are there any plans to support **custom_eval** and **custom_obj**? @param custom_eval Customized evaluation function provided by user. Currently unsupported. @param custom_obj Customized objective function provided by user. Currently unsupported.

Any plans to update the papers from [KDD MILETS Workshop](https://kdd-milets.github.io/milets2024/#call)?

Implement Bernstein-Flow

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Add Bernstein-Flow https://github.com/kashif/gluon-ts/blob/bernstein/src/gluonts/torch/distributions/bernstein_quantile.py#L30C5-L30C88 https://github.com/alexshtf/alexshtf.github.io/blob/master/assets/shape_constrained_models.ipynb